Systems and methods for light detection and ranging (lidar) based generation of an inventory list of personal belongings

ABSTRACT

The following relates generally to light detection and ranging (LIDAR). In some embodiments, an inventory list of personal belongings is generated based upon data received from a LIDAR camera. For instance, in some embodiments a system: receives LIDAR data generated from one or more LIDAR cameras; analyzes the LIDAR data to determine or identify one or more personal articles or insurable assets; and generates an electronic inventory list of personal belongings based upon the one or more personal articles or insurable assets determined or identified from the LIDAR data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Pat. Application No.17/185,896, entitled “SYSTEMS AND METHODS FOR LIGHT DETECTION ANDRANGING (LIDAR) BASED GENERATION OF AN INVENTORY LIST OF PERSONALBELONGINGS,” filed Feb. 25, 2021 which claims the benefit of U.S.Provisional Application No. 62/983,368, entitled “SYSTEMS AND METHODSFOR LIGHT DETECTION AND RANGING (LIDAR),” filed Feb. 28, 2020; U.S.Provisional Application No. 62/991,461, entitled “SYSTEMS AND METHODSFOR LIGHT DETECTION AND RANGING (LIDAR),” filed Mar. 18, 2020; and U.S.Provisional Application No. 62/994,201, entitled “YSTEMS AND METHODS FORLIGHT DETECTION AND RANGING (LIDAR),” filed Mar. 24, 2020, the entiretyof each of which is incorporated by reference herein.

FIELD

The present disclosure generally relates to light detection and ranging(LIDAR) technology, and more specifically to applications of LIDARtechnology to insurance policies and applications of LIDAR technology toassist an impaired individual.

BACKGROUND

LIDAR is a technology that measures distance to a target by illuminatingthe target (e.g., using laser light) and then measuring the reflectedlight with a sensor (e.g., measuring the time of flight from the lasersignal source to its return to the sensor). Digital 3D representationsof the target may then be made using differences in laser return timesand wavelengths. LIDAR may be used to measure distances (e.g., thedistance from a LIDAR camera to an object, the distance between objects,and so forth).

SUMMARY

The present embodiments may be related to LIDAR technology, includingapplications of LIDAR technology to insurance policies and applicationsof LIDAR technology to assist an impaired individual. The LIDARtechnology may be used to produce an insurance quote or insurance claim.The LIDAR technology may also be used to provide navigation directionsto assist an impaired individual.

In accordance with the described embodiments, the disclosure hereingenerally addresses, inter alia, systems and methods for applying LIDARtechnology to insurance quote generation (e.g., a quote for homeinsurance). A server may receive preexisting architecture data, createbaseline architecture data using the preexisting architecture data,receive LIDAR data generated from a LIDAR camera, combine the baselinearchitecture data with the LIDAR data to create an architecture profile,and generate an insurance quote based upon the architecture profile.According to some aspects, the LIDAR data comprises a 3D point cloud,and may include information of both an interior and an exterior of ahouse. The server may also receive information from other sources, suchas drones.

In one aspect, a computer-implemented method for generating an insurancequote may be provided. The computer-implemented method may include, viaone or more local or remote processors, transceivers, sensors, and/orservers, (1) receiving preexisting architecture data; (2) creatingbaseline architecture data using the preexisting architecture data; (3)receiving LIDAR data generated from a LIDAR camera; (4) combining thebaseline architecture data with the LIDAR data to create an architectureprofile; and/or (5) generating an insurance quote based upon thearchitecture profile. The method may include additional, less, oralternate actions, including that discussed elsewhere herein.

In another aspect, an electronic device for generating an insurancequote may be provided. The electronic device may be configured to, viaone or more processors, transceivers, and/or sensors, (1) receivepreexisting architecture data; (2) create baseline architecture datausing the preexisting architecture data; (3) receive LIDAR datagenerated from a LIDAR camera; (4) combine the baseline architecturedata with the LIDAR data to create an architecture profile; and/or (5)generate an insurance quote based upon the architecture profile. Theelectronic device may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In yet another aspect, a computer system for generating an insurancequote may be provided. The system may include a LIDAR camera, a memoryconfigured to store non-transitory computer executable instructions andconfigured to interface with a processor and/or associated transceiver.The processor may be configured to execute the non-transitory computerexecutable instructions to cause the processor and/or associatedtransceiver to (1) receive preexisting architecture data; (2) createbaseline architecture data using the preexisting architecture data; (3)receive LIDAR data generated from a LIDAR camera; (4) combine thebaseline architecture data with the LIDAR data to create an architectureprofile; and/or (5) generate an insurance quote based upon thearchitecture profile. The system may include additional, less, oralternate functionality, including that discussed elsewhere herein.

In accordance with the described embodiments, the disclosure hereingenerally addresses, inter alia, systems and methods for applying LIDARtechnology to generate an inventory list of personal belongings. Aserver may (1) receive light detection and ranging (LIDAR) datagenerated from one or more LIDAR cameras; (2) analyze the LIDAR data todetermine or identify one or more personal articles or insurable assets;and/or (3) generate an electronic inventory list of personal belongingsbased upon the one or more personal articles or insurable assetsdetermined or identified from the LIDAR data.

In accordance with the described embodiments, the disclosure hereingenerally addresses, inter alia, systems and methods for applying LIDARtechnology to generate a homeowner’s insurance quote. A server may (1)receive light detection and ranging (LIDAR) data generated from one ormore LIDAR cameras; (2) analyze the LIDAR data to determine or identifyone or more features or characteristics of a home; and/or (3) generatean electronic homeowners insurance quote based upon, at least in part,the one or more features or characteristics of the home determined oridentified from the LIDAR data.

Further in accordance with the described embodiments, the disclosureherein generally addresses, inter alia, systems and methods for applyingLIDAR technology to insurance claim generation (e.g., providing firstnotice of loss, or first notice of an insurance claim). A server may (1)receive LIDAR data generated from a LIDAR camera; (2) determine if anevent has occurred based upon the received LIDAR data; and/or (3) if theevent has occurred, generate and provide an electronic or virtual firstnotice of loss (or otherwise first notice of an insurance claim orpotential insurance claim). The server may also receive information fromother sources, such as drones, smart vehicles, smart homes, vehiclesensors, home-mounted sensors, smart infrastructure, mobile devices,mobile device sensors, and smart devices.

In another aspect, a computer-implemented method for generating anelectronic first notice of loss may be provided. The method may include,via one or more local or remote processors, transceivers, sensors,and/or servers, (1) receiving LIDAR data generated from a LIDAR camera;(2) determining that an event has occurred based upon the received LIDARdata; and/or (3) in response to the determination that the event hasoccurred, generating and providing an electronic first notice of loss.The first notice of loss may be provided to an insurance provider’sand/or an insured’s computing device. For instance, an electronic firstnotice of loss may be transmitted to an insurance provider server or aninsured’s mobile device, and then displayed for review and furtheraction, such as completing, preparing, and/or handling an insuranceclaim. The method may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In yet another aspect, an electronic device for generating an electronicfirst notice of loss may be provided. The electronic device may beconfigured to receive LIDAR data generated from a LIDAR camera,determine if an event has occurred based upon the received LIDAR data,and if the event has occurred, generate, provide, and/or display anelectronic first notice of loss.

In yet another aspect, a computer system for generating an electronic(or virtual) first notice of loss may be provided. The system mayinclude a LIDAR camera, a memory configured to store non-transitorycomputer executable instructions and configured to interface with aprocessor. The processor may be configured to execute the non-transitorycomputer executable instructions to cause the processor and/or anassociated transceiver to (1) receive LIDAR data generated from theLIDAR camera; (2) determine if an event has occurred based upon thereceived LIDAR data; and (3) if the event has occurred, generate andprovide an electronic first notice of loss. The first notice of loss maybe provided to an insurance provider’s and/or an insured’s computingdevice. For instance, an electronic first notice of loss may betransmitted to an insurance provider server or an insured’s mobiledevice, and then displayed for review and further action, such ascompleting, preparing, or handling an insurance claim. The computersystem may include additional, less, or alternate functionality,including that discussed elsewhere herein.

Further in accordance with the described embodiments, the disclosureherein generally addresses, inter alia, systems and methods for applyingLIDAR technology to assist an impaired individual (e.g., a visionimpaired individual). A server may receive LIDAR data generated from theLIDAR camera, and provide navigation feedback to a human individualbased upon the LIDAR data. According to some aspects, the navigationfeedback may be auditory or visual, and include direction and distanceinstructions to guide the human individual. The LIDAR data may begenerated from a LIDAR camera harnessed to the human individual.

In yet another aspect, a computer-implemented method for assisting animpaired individual may be provided. The computer-implemented method mayinclude, via one or more local or remote processors, transceivers,sensors, and/or servers, (1) receiving LIDAR data generated from a LIDARcamera, and/or (2) generating and/or providing navigation feedback to ahuman individual based upon the LIDAR data. The method may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

In yet another aspect, an electronic device for assisting an impairedindividual may be provided. The electronic device may be configured to,via one or more processors, transceivers, and/or sensors, receive LIDARdata generated from the LIDAR camera, and/or generate and providenavigation feedback to a human individual based upon the LIDAR data.

In yet another aspect, a computer system for assisting an impairedindividual may be provided. The system may include a LIDAR cameraconfigured to be harnessed to a human individual, and a memoryconfigured to store non-transitory computer executable instructions andconfigured to interface with a processor. The processor may beconfigured to execute the non-transitory computer executableinstructions to cause the processor and/or an associated transceiver toreceive LIDAR data generated from the LIDAR camera, and/or generate andprovide navigation feedback to a human individual based upon the LIDARdata. The system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

Advantages will become apparent to those skilled in the art from thefollowing description. For example, in one aspect, the systems andmethods disclosed herein advantageously produce a more accurateinsurance quote than prior systems. In another aspect, the systems andmethods disclosed herein advantageously provide a more accurateinsurance claim to an insurance company than prior systems. In anotheraspect, a further advantage of the systems and methods disclosed hereinis to provide faster first notice of loss to an insurance company thanprior systems. In another aspect, a further advantage of the systems andmethods disclosed herein is to provide an improved navigation system forimpaired individuals (e.g., visually impaired individuals). Furtheradvantages will become apparent to those of ordinary skill in the artfrom the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred embodiments which have beenshown and described by way of illustration. As will be realized, thepresent embodiments may be capable of other and different embodiments,and their details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

The Figures described below depict various aspects of the applications,methods, and systems disclosed herein. It should be understood that eachFigure depicts an embodiment of a particular aspect of the disclosedapplications, systems and methods, and that each of the Figures isintended to accord with a possible embodiment thereof. Furthermore,wherever possible, the following description refers to the referencenumerals included in the following Figures, in which features depictedin multiple Figures are designated with consistent reference numerals.

FIG. 1 shows an exemplary embodiment relating to determining a quote forhome insurance.

FIG. 2 shows a flowchart of an example of generating an insurance quote.

FIG. 3A shows an exemplary embodiment relating to determining aninsurance claim.

FIG. 3B shows an exemplary embodiment relating to determining aninsurance claim, and including an in home hub.

FIG. 4 shows a flowchart of an example of providing first notice of lossto an insurance company.

FIG. 5A shows an exemplary computer system to aide an impaired humanindividual.

FIG. 5B shows an exemplary computer system to aide an impaired humanindividual where some data is sent to home hub 320 before being sent toservers 110 c.

FIG. 6 shows a flowchart of an example of providing feedback to animpaired human individual.

FIG. 7 illustrates a flow diagram of an exemplary computer-implementedmethod of generating a personal articles insurance quote in accordancewith the presently described embodiments.

FIG. 8 illustrates a flow diagram of an exemplary computer-implementedmethod of generating an inventory list of personal belongings inaccordance with the presently described embodiments.

FIG. 9 illustrates a flow diagram of an exemplary computer-implementedmethod of generating a homeowners insurance quote in accordance with thepresently described embodiments.

FIG. 10 illustrates a flow diagram of an exemplary computer-implementedmethod of insurance claim generation from LIDAR data in accordance withthe presently described embodiments.

FIG. 11 illustrates a flow diagram of an exemplary computer-implementedmethod of providing first notice of loss in accordance with thepresently described embodiments.

FIG. 12 illustrates a flow diagram of an exemplary computer-implementedmethod of navigation for the vision impaired in accordance with thepresently described embodiments.

DETAILED DESCRIPTION

The present embodiments relate to, inter alia: (i) LIDAR technology;(ii) producing an insurance quote; (iii) producing an insurance claim;and (iv) technology for aiding an impaired individual.

LIDAR is a technology that measures distance to a target by illuminatingthe target (e.g., using laser light) and then measuring the reflectedlight with a sensor (e.g., measuring the time of flight from the lasersignal source to its return to the sensor). Digital 3D representationsof the target can then be made using differences in laser return timesand wavelengths. LIDAR may be used to measure distances (e.g., thedistance from a LIDAR camera to an object, the distance between objects,and so forth).

In this respect, LIDAR may create a 3D point cloud model (e.g., a set ofdata points in space) of a room or landscape by measuring many points inthe room or landscape. Furthermore, as is understood in the art, 3Dpoint clouds may be converted to 3D surfaces (e.g., by using techniquessuch as Delaunay triangulation, alpha shapes, or ball pivoting to builda network of triangles over existing vertices of the point cloud).

In this regard, some embodiments leverage this LIDAR information toproduce a home insurance quote (or an insurance quote for anystructure/building/architecture besides a home).

Exemplary Insurance Quote Generation System

FIG. 1 shows servers 110 a (e.g., servers of an insurance company)sending and receiving information with LIDAR camera 120. The gathereddata may include the dimensions of the house, including dimensions ofpart or all of the interior and exterior of the house. The LIDAR datamay be used to create a partial or complete home map, and may include 3Dpoint cloud(s) created from the LIDAR data. The LIDAR camera 120 may beoperated by any human or machine.

In some embodiments, the LIDAR camera 120 is operated by an employee ofthe insurance company. For example, an insurance company employee maybring a LIDAR camera 120 to a house, and gather data on the house.Advantageously, LIDAR data could be analyzed at an office or elsewhereoffsite from the home, thereby allowing the insurance company employeeto spend only a small amount of time on a home premises (e.g., theinsurance company employee could simply gather the LIDAR data and thenleave the premises).

In other embodiments, this same LIDAR data is gathered by anotherindividual besides an insurance company employee. For example, the LIDARdata may be gathered by a prospective home insurance purchaser.

The LIDAR data may be sent to the servers 110 a by any method. Forexample, the LIDAR data may be sent to the servers 110 a directly fromthe LIDAR camera 120 via the internet. In another example, the LIDARdata may be transferred from the LIDAR camera 120 to a computer (via,e.g., a cable, a USB device, or any other means), and then sent from thecomputer to the servers 110 a by any methods (e.g., sent by theinternet, by Ethernet connection, or so forth).

Each server 110 a may include one or more computer processors adaptedand configured to execute various software applications and componentsof insurance quote generation system 100, in addition to other softwareapplications. The server 110 a may further include a database 146, whichmay be adapted to store data related to the LIDAR camera 120, as well asany other data. The server 110 a may access data stored in the database146 when executing various functions and tasks associated with LIDARtechnology and generating insurance quotes.

Although the insurance quote generation system 100 is illustrated toinclude one LIDAR camera 120, one drone 140, and one group of servers110 a (FIG. 1 is illustrated to show three servers 110 a, but it shouldbe understood that the server(s) 110 a may be one or more server(s)), itshould be understood that different numbers LIDAR camera 120, drone 140,and/or servers 110 a may be utilized. For instance, the system 100 mayinclude a plurality of servers 110 a and hundreds of mobile LIDARcameras 120 or drones 140. Furthermore, the database storage orprocessing performed by the one or more servers 110 a may be distributedamong a plurality of servers 110 a in an arrangement known as “cloudcomputing.” This configuration may provide various advantages, such asenabling near real-time uploads and downloads of information as well asperiodic uploads and downloads of information.

The server 110 a may have a controller 155 that is operatively connectedto the database 146 via a link 156. It should be noted that, while notshown, additional databases may be linked to the controller 155 in aknown manner. For instance, separate databases may be used for storingdifferent types of information and/or making different calculations. Thecontroller 155 may include a program memory 160, a processor 162 (whichmay be called a microcontroller or a microprocessor), a random-accessmemory (RAM) 164, and an input/output (I/O) circuit 166, all of whichmay be interconnected via an address/data bus 165. It should beappreciated that although only one microprocessor 162 is shown, thecontroller 155 may include multiple microprocessors 162. Similarly, thememory of the controller 155 may include multiple RAMs 164 and multipleprogram memories 160. Although the I/O circuit 166 is shown as a singleblock, it should be appreciated that the I/O circuit 166 may include anumber of different types of I/O circuits. The RAM 164 and programmemories 160 may be implemented as semiconductor memories, magneticallyreadable memories, or optically readable memories, for example.

The server 110 a may further include a number of software applicationsstored in a program memory 160. The various software applications on theserver 110 a may include a LIDAR data monitoring application 141 forreceiving information from LIDAR camera 120, a drone data monitoringapplication 142 for monitoring drone data, a receiving preexisting housedata application 143, an architecture application 144 for creatingbaseline architecture data, and an insurance quote generationapplication 145 for generating an insurance quote. The various softwareapplications may be executed on the same computer processor or ondifferent computer processors. The servers 110 a also gather data fromother sources. For instance, the servers 110 a also gather data frompreexisting sources that have data on the home. For instance, data maybe gathered from public records, property deeds, government records,realtors (e.g., from websites and apps that realtors post informationto), previous insurance claims, and so forth.

The servers 110 a also gather data from other sources. For example, theservers 110 a also gather data from preexisting sources that have dataon the home. For instance, data may be gathered from public records,property deeds, government records, realtors (e.g., from websites andapps that realtors post information to), previous insurance claims, andso forth.

The servers 110 a also gather data from a drone 140. Such data mayinclude data from a camera on the drone, a LIDAR camera on the drone,radio detection and ranging (RADAR) data gathered by the drone, globalpositioning system (GPS) data gathered by the drone, information from aninfrared camera of the drone, and so forth.

A machine learning algorithm may be used to analyze any or all of thedata held by servers 110 a. The machine learning algorithm may be asupervised learning algorithm, employ decision trees, make use of anartificial neural network, make use of Bayesian statistical analysis, orcombinations thereof. In this regard, a processor or a processingelement may be trained using supervised or unsupervised machinelearning, and the machine learning program may employ a neural network,which may be a convolutional neural network, a deep learning neuralnetwork, or a combined learning module or program that learns in two ormore fields or areas of interest. Machine learning may involveidentifying and recognizing patterns in existing data in order tofacilitate making predictions for subsequent data. Models may be createdbased upon example inputs in order to make valid and reliablepredictions for novel inputs.

In some embodiments, the preexisting house data 130 is used to createbaseline data for the house. The baseline data is then combined with theLIDAR camera data 120 to create a house profile, which in turn may beused to generate an insurance quote for the house.

It should be understood that, over time, the servers 110 a mayaccumulate a large pool of data on an individual home or a group ofhomes.

The data described above may be used (e.g., with a machine learningalgorithm described above or by any other technique) to generate aninsurance quote for home insurance. The machine learning algorithm maybe trained using previously known home data along with previousinsurance quotes.

The data described above may be used (e.g., with a machine learningalgorithm described above or by any other technique) to predict thelikelihood of an adverse event occurring to the home (e.g., fire, flood,wind damage, or so forth).

Exemplary Insurance Quote Generation Method

FIG. 2 shows a flowchart of an example of generating an insurance quote.With reference thereto, at step 210, the preexisting house data 130 issent to servers 110 a. At step 220, the preexisting house data is usedto create a baseline data of the house. At step 230, data from the LIDARcamera 120 is sent to the servers 110 a. At step 240, drone data is sentto the servers 110 a. At step 250, a house profile is created based uponany or all of the baseline data, LIDAR data, and drone data. In anoptional step 255, a machine learning algorithm is trained. At step 260,an insurance quote is generated based upon the house profile. Theinsurance quote may be generated using the trained machine learningalgorithm or by any other technique.

Optionally, the insurance company may offer a discount to a home ownerif the home owner allows LIDAR data of the house to be collected. Inthis regard, an insurance customer may opt-in to a rewards, insurancediscount, or other type of program. After the insurance customerprovides their affirmative consent, an insurance provider remote server,such as servers 110 a, may collect data from the customer’s mobiledevice, smart home controller, or other smart devices - such as with thecustomer’s permission or affirmative consent. The data collected mayalso be related to smart home functionality (or home occupantpreferences or preference profiles), and/or insured assets before(and/or after) an insurance-related event, including those eventsdiscussed elsewhere herein. In return, risk averse insureds, homeowners, or home or apartment occupants may receive discounts orinsurance cost savings related to home, renters, personal articles,auto, and/or other types of insurance from the insurance provider.

Further in this regard, in one aspect, smart or interconnected homedata, and/or other data, including the types of data discussed elsewhereherein, may be collected or received by an insurance provider remoteserver, such as via direct or indirect wireless communication or datatransmission from a smart home controller, mobile device, or othercustomer computing device, after a customer affirmatively consents orotherwise opts-in to an insurance discount, reward, or other program.The insurance provider may then analyze the data received with thecustomer’s permission to provide benefits to the customer. As a result,risk averse customers may receive insurance discounts or other insurancecost savings based upon data that reflects low risk behavior and/ortechnology that mitigates or prevents risk to (i) insured assets, suchas homes, personal belongings, or vehicles, and/or (ii) home orapartment occupants.

Exemplary Insurance Claim Generation System

In another aspect, in addition to generating an insurance quote,techniques for determining an insurance claim are contemplated; thetechniques greatly expedite the insurance claims process, and will bedescribed as follows. With reference to FIG. 3A, LIDAR camera 120 may bepositioned in a home. It should be understood that the illustrated LIDARcamera 120 may represent a single LIDAR camera or multiple LIDAR cameraspositioned throughout the home. The LIDAR camera 120 may be set up byany human or machine. In some embodiments, the LIDAR camera 120 is setup by an insurance company employee. In other embodiments, the LIDARcamera 120 is set up by a home owner using instructions from theinsurance company; for example, the instructions may be sent by aninsurance company via an app, website, paper mailing, or any othertechnique. In some embodiments, the LIDAR camera 120 provides real timedata to the servers 110 b.

Further regarding FIG. 3A, smart devices 310 also send smart device datato the servers 110 b. The smart devices 310 may include, for example:speakers, cameras, lights, microphones, radios, thermostats,toothbrushes, motion sensors, infrared sensors, or any other devices. Inthe example of FIG. 3B, the smart devices 310 and LIDAR camera 120 senddata to an in home hub 320, which in turn sends the collected data toservers 110 b. In some embodiments, the in home hub sends the data tothe servers 110 b in real time; in other embodiments, the in home hub320 collects data, and then sends the data in batches to the servers 110b.

With continuing reference to FIGS. 3A and 3B, the servers 110 b may alsoreceive data from drone 140 and preexisting house data 130. Each server110 b may include one or more computer processors adapted and configuredto execute various software applications and components of insuranceclaim generation systems 300 a, 300 b, in addition to other softwareapplications. The server 110 b may further include a database 146, whichmay be adapted to store data related to the LIDAR camera 120, as well asany other data. The server 110 b may access data stored in the database146 when executing various functions and tasks associated with LIDARtechnology and generating insurance claims and/or providing first noticeof insurance claims.

Although the insurance claim generation systems 300 a, 300 b areillustrated to include one LIDAR camera 120, one drone 140, one group ofsmart devices 310, and one group of servers 110 b (FIGS. 3A and 3B areeach illustrated to show three servers 110 b, but it should beunderstood that the server(s) 110 b may be one or more server(s)), itshould be understood that different numbers of LIDAR camera 120, drone140, and/or servers 110 b may be utilized. For instance, the system 100may include a plurality of servers 110 b and hundreds of mobile LIDARcameras 120 or drones 140. Furthermore, the database storage orprocessing performed by the one or more servers 110 b may be distributedamong a plurality of servers 110 b in an arrangement known as “cloudcomputing.” This configuration may provide various advantages, such asenabling near real-time uploads and downloads of information as well asperiodic uploads and downloads of information.

The server 110 b may have a controller 155 that is operatively connectedto the database 146 via a link 156. It should be noted that, while notshown, additional databases may be linked to the controller 155 in aknown manner. For instance, separate databases may be used for storingdifferent types of information and/or making different calculations. Thecontroller 155 may include a program memory 160, a processor 162 (whichmay be called a microcontroller or a microprocessor), a random-accessmemory (RAM) 164, and an input/output (I/O) circuit 166, all of whichmay be interconnected via an address/data bus 165. It should beappreciated that although only one microprocessor 162 is shown, thecontroller 155 may include multiple microprocessors 162. Similarly, thememory of the controller 155 may include multiple RAMs 164 and multipleprogram memories 160. Although the I/O circuit 166 is shown as a singleblock, it should be appreciated that the I/O circuit 166 may include anumber of different types of I/O circuits. The RAM 164 and programmemories 160 may be implemented as semiconductor memories, magneticallyreadable memories, or optically readable memories, for example.

The server 110 b may further include a number of software applicationsstored in a program memory 160. The various software applications on theserver 110 b may include a LIDAR data monitoring application 141 forreceiving information from LIDAR camera 120, a drone data monitoringapplication 142 for monitoring drone data, a receiving preexisting housedata application 143, a smart device receiving application 301 forreceiving smart device data, an insurance claim generation application302 for generating an insurance claim, and first notice providingapplication 303 for providing first notice of an insurance claim. Thevarious software applications may be executed on the same computerprocessor or on different computer processors. It should be understoodthat, over time, the servers 110 b may accumulate a large pool of dataon an individual home or a group of homes.

The servers 110 b may also receive data from drone 140 and preexistinghouse data 130. It should be understood that, over time, the servers 110b may accumulate a large pool of data on an individual home or a groupof homes.

A machine learning algorithm may be used to analyze any or all of thedata held by servers 110 b. The machine learning algorithm may be asupervised learning algorithm, employ decision trees, make use of anartificial neural network, make use of Bayesian statistical analysis, orcombinations thereof. In this regard, a processor or a processingelement may be trained using supervised or unsupervised machinelearning, and the machine learning program may employ a neural network,which may be a convolutional neural network, a deep learning neuralnetwork, or a combined learning module or program that learns in two ormore fields or areas of interest. Machine learning may involveidentifying and recognizing patterns in existing data in order tofacilitate making predictions for subsequent data. Models may be createdbased upon example inputs in order to make valid and reliablepredictions for novel inputs.

The servers 110 b may use any of the received data to provide firstnotice of loss (e.g., by using a machine learning algorithm describedabove or by any other technique). For example, the servers 110 b may usethe received data to determine that an event relating to any of thefollowing has occurred: fire, flood, wind, or burglary. Any of thereceived data may be used alone or in combination with any of the otherreceived data to determine if an event has occurred. For example, datafrom the LIDAR camera 120 alone may be used to determine that high windshave broken a window; alternatively, in another example, data from theLIDAR camera 120 combined with data from a smart speaker may be used todetermine that high winds have broken a window.

In another example, a machine learning algorithm is trained usingpreviously known data (e.g., previously known LIDAR data, housedimensional data, drone data, smart device information data, and soforth); subsequently, real time LIDAR data from LIDAR camera 120 isinput into the machine learning algorithm which determines that an eventhas occurred (e.g., a fire, flood, damage from hail, damage from wind orso forth); and first notice is then provided to the insurance company.

Any of the data received by the servers 110 b can also be used todetermine that a repair on a house has been completed (e.g., drywall hasbeen repaired, a replacement window has been installed, or so forth).This is most often done after first notice to the insurance company wasprovided, and the claims process is underway or completed. The homeowner may also provide notice to the insurance company that a repair hasbeen completed. In this regard, the user may add comments to or annotateLIDAR data or other smart device data indicating that a repair iscomplete; for example, the annotations may be entered on an insurancecompany app.

Optionally, the insurance company may offer a discount to a home ownerif the home owner allows LIDAR data of the house to be collected. Inthis regard, the user may install the LIDAR camera(s) about the homeaccording to instructions provided by the insurance company, and thensubsequently receive the insurance discount. In this way, an insurancecustomer may opt-in to a rewards, insurance discount, or other type ofprogram. After the insurance customer provides their affirmativeconsent, an insurance provider remote server, such as servers 110 b, maycollect data from the customer’s mobile device, smart home controller,or other smart devices - such as with the customer’s permission oraffirmative consent. The data collected may also be related to smarthome functionality (or home occupant preferences or preferenceprofiles), and/or insured assets before (and/or after) aninsurance-related event, including those events discussed elsewhereherein. In return, risk averse insureds, home owners, or home orapartment occupants may receive discounts or insurance cost savingsrelated to home, renters, personal articles, auto, and/or other types ofinsurance from the insurance provider.

Further in this regard, in one aspect, smart or interconnected homedata, and/or other data, including the types of data discussed elsewhereherein, may be collected or received by an insurance provider remoteserver, such as via direct or indirect wireless communication or datatransmission from a smart home controller, mobile device, or othercustomer computing device, after a customer affirmatively consents orotherwise opts-in to an insurance discount, reward, or other program.The insurance provider may then analyze the data received with thecustomer’s permission to provide benefits to the customer. As a result,risk averse customers may receive insurance discounts or other insurancecost savings based upon data that reflects low risk behavior and/ortechnology that mitigates or prevents risk to (i) insured assets, suchas homes, personal belongings, or vehicles, and/or (ii) home orapartment occupants.

Exemplary Insurance Claim Generation Method

FIG. 4 shows a flowchart of an example of providing first notice to aninsurance company. With reference thereto, at step 410, an insurancecompany provides instructions to a home owner (e.g., via an app,website, paper mailing, or any other technique) on how to set up a LIDARcamera. The LIDAR camera itself may also be provided to the home ownerat this point. At step 415, known house data is provided to theinsurance company. At step 420, LIDAR data from the LIDAR camera(possibly through a home hub) is received by the insurance company. Atstep 425, drone data from a drone is received by the insurance company.At step 430, smart device data from a smart device or from a home hub isreceived by the insurance company. At step 435, servers determine thatan event has occurred (e.g., using a machine learning algorithm). Atstep 440, first notice to an insurance company occurs. For example, thedetermination that an event has occurred is effectively the first noticeof loss, or first notice of potential loss, to the insurance company.

In certain embodiments, the first notice of loss may be provided to aninsurance provider’s and/or an insured’s computing device. For instance,an electronic first notice of loss may be transmitted to an insuranceprovider server or an insured’s mobile device, and then displayed forreview and further action, such as completing, preparing, or handling aninsurance claim.

At step 445, a determination (based upon, e.g., the known house, LIDAR,drone, and/or smart device data) is made as to the cost of a repair tosatisfy the insurance claim. For instance, repair or replacement cost ofone or more home features or characteristics may be estimated fromprocessor analysis of LIDAR data and/or smart home sensor data. At step450, a repair on the house is made to satisfy the insurance claim. Atstep 455, updated LIDAR, drone and/or smart device data is sent to theinsurance company. At step 460, based upon updated LIDAR, drone, orsmart device data, a determination is made that a repair to the househas been done to satisfy insurance claim.

In addition, although the foregoing refers to home insurance, it shouldbe understood that any of the foregoing techniques may also be appliedto insurance for buildings other than homes (e.g., applied to insurancefor a building used for operation of a business, or any otherbuilding/structure/architecture/construction).

Exemplary System for Assisting an Impaired Individual

In another aspect, a LIDAR camera may be used to aide an individual. Forexample, a LIDAR camera may be used to aide an individual with a visionimpairment or other disability. With reference to FIG. 5A, a LIDARcamera 510 harnessed to an individual provides data to servers 110 c.Another (possibly stationary) LIDAR camera 520 also provides data toservers 110 c. The individual’s smartphone 530 also sends data, whichmay include, for example, GPS data, camera data, LIDAR data, and soforth to the servers 110 c. With reference to FIG. 5B, data is sent tothe servers 110 c via an in home hub 320.

The data gathered by servers 110 c may be used to aid an individual. Theindividual may or may not have a LIDAR camera 510 harnessed to herself.The aide provided may be in any form. For example, for an individual maybe provided with auditory instructions on how to navigate a room. Forinstance, if the individual is walking towards an object (e.g., atable), the individual may receive an auditory warning that she isapproaching the object, further receive auditory information on howclose the object is (e.g., “a table is five feet in front of you”), andfurther receive auditory instructions on how to avoid the object (e.g.,“move three feet to the left,” or “turn 90 degrees to the left and thenwalk three feet”). In this regard, the auditory instructions may specifya direction and a distance for the individual to move.

The audio feedback may be provided to the individual through theindividual’s smartphone or though smart home devices such as smartspeakers. Thus, smart speakers may direct an individual on ways tonavigate a home. In addition, LIDAR cameras are able to detect rapidlymoving objects. Thus, in some embodiments, if there is an object movingtowards the individual, instructions are provided to the user on how toavoid the object. In some embodiments, a warning or notification that anobject is approaching the individual is sent to the individual, and thewarning or notification may be audio, visual, or haptic (e.g., theindividual’s smartphone vibrating).

In addition, GPS data from the individual’s smartphone or mobile deviceor wearables, or from any other GPS device may be used to augment theLIDAR and other data.

Feedback may be provided to the individual even when the individual isnot in the home. For example, if the LIDAR camera is harnessed to theindividual, and the LIDAR detects that the individual is approaching acrosswalk and there is an approaching vehicle or object, feedback may begiven to the individual not to enter the crosswalk. In this example, thefeedback may be in the form of a warning or notification or in any otherform. In another example, when the individual is outside the home, audiofeedback may be provided to the individual through an earpiece.

In addition to auditory feedback, the feedback may also be visual, orhaptic. For example, haptic feedback (e.g., the individual’s smartphone530 vibrating, or the individual’s device holding the LIDAR camera 520vibrating) may be generated if the individual is approaching an object.In one example of visual feedback, a visual warning that there is afire, flood or structural damage (e.g., a window destroyed due to highwind or hail) may be generated. Visual feedback is primarily useful ifthe individual is not vision impaired.

The aide provided to the individual may be further based upon data fromsmart devices 310, from drone 140, or from an individual’s smartphone ormobile device 530, or from an individual smart glasses or other wearabledevices. Furthermore, the aide may be based upon preexisting house data130, which may include a 3D map of all or part of the house. In thisrespect, the 3D map may be made from 3D point cloud(s) of the house thatwere made at any time (e.g., made as part of producing an insurancequote or insurance claim).

Further regarding FIGS. 5A and 5B, each server 110 c may include one ormore computer processors adapted and configured to execute varioussoftware applications and components of systems 500 a, 500 b forassisting an impaired individual, in addition to other softwareapplications. The server 110 c may further include a database 146, whichmay be adapted to store data related to the LIDAR camera harnessed to anindividual 510, and/or LIDAR camera in building 520, as well as anyother data. The server 110 c may access data stored in the database 146when executing various functions and tasks associated with LIDARtechnology and providing assistance to an impaired individual.

Although the systems 500 a, 500 b are illustrated to include one LIDARcamera harnessed to an individual 510, one LIDAR camera in building 520,one individual’s smartphone 530, one group of smart devices 310, onedrone 140, and one group of servers 110 c (FIGS. 5A and 5B are eachillustrated to show three servers 110 c, but it should be understoodthat the server(s) 110 c may be one or more server(s)), it should beunderstood that different numbers of these items may be utilized. Forinstance, the system 100 may include a plurality of servers 110 c andhundreds of mobile LIDAR cameras 120 or drones 140. Furthermore, thedatabase storage or processing performed by the one or more servers 110c may be distributed among a plurality of servers 110 c in anarrangement known as “cloud computing.” This configuration may providevarious advantages, such as enabling near real-time uploads anddownloads of information as well as periodic uploads and downloads ofinformation.

The server 110 c may have a controller 155 that is operatively connectedto the database 146 via a link 156. It should be noted that, while notshown, additional databases may be linked to the controller 155 in aknown manner. For instance, separate databases may be used for storingdifferent types of information and/or making different calculations. Thecontroller 155 may include a program memory 160, a processor 162 (whichmay be called a microcontroller or a microprocessor), a random-accessmemory (RAM) 164, and an input/output (I/O) circuit 166, all of whichmay be interconnected via an address/data bus 165. It should beappreciated that although only one microprocessor 162 is shown, thecontroller 155 may include multiple microprocessors 162. Similarly, thememory of the controller 155 may include multiple RAMs 164 and multipleprogram memories 160. Although the I/O circuit 166 is shown as a singleblock, it should be appreciated that the I/O circuit 166 may include anumber of different types of I/O circuits. The RAM 164 and programmemories 160 may be implemented as semiconductor memories, magneticallyreadable memories, or optically readable memories, for example.

The server 110 c may further include a number of software applicationsstored in a program memory 160. The various software applications on theserver 110 c may include, a drone data monitoring application 142 formonitoring drone data, a receiving preexisting house data application143, a smart device receiving application 301 for receiving smart devicedata, a LIDAR camera harnessed to individual receiving application 501for receiving LIDAR data from a LIDAR camera harnessed to an individual510, a LIDAR camera in building application 502 for receiving LIDAR datafrom a LIDAR camera in building 520, individual’s smartphone receivingapplication 503 for receiving data from an individual’s smartphone 530,and feedback determination application 504 for determining feedback. Thevarious software applications may be executed on the same computerprocessor or on different computer processors.

Exemplary Method for Assisting an Impaired Individual

FIG. 6 shows a flowchart of an example of providing assistance to animpaired individual (e.g., providing navigation instructions to a visionimpaired individual). With reference thereto, at step 610, a LIDARcamera is harnessed to an impaired individual, or may be implanted into,or configured as part of, a wearable device, smart glasses, or smartheadgear. At step 615, known house or room dimensional data (or otherarchitectural data) is gathered and/or received. In some embodiments,house or room dimensional data may be generated from smart home ormobile device data, such as by processor analysis of smart home sensordata or camera images.

At step 620, LIDAR data is received from the LIDAR camera harnessed tothe impaired individual, or otherwise worn by the individual. At step625, LIDAR data is received from a LIDAR camera stationed in a home. Forinstance, one or more LIDAR cameras may be home-mounted andinterconnected with a smart home controller, or other computing device,via one or more radio frequency links and/or wireless communicationcomputing network.

At step 630, information from one or more smart devices is received. Forinstance, the smart devices may include smart sensors, smart cameras,mobile devices, wearables, or other computing devices. The smart devicesmay include processors and transceivers, and be configured for wirelesscommunication or data transmission, such as a home computing network.

At step 635, drone data may be received. For instance, small dronesconfigured with cameras, sensors, and/or transceivers may gather imageand sensor data and transmit that data to a smart home controller, orother user computing device. The small drones may be configured toautonomously fly about the inside and/or outside of the home, and gathersensor and image data.

At step 640, navigation feedback is determined. For instance, a smarthome controller that is collecting and receiving various sensor andimage data, including LIDAR data, as well as mobile device data, smarthome sensor and image data, drone data, wearable data, etc., may analyzethat data. The smart home controller may determine which room a visionimpaired individual is located, a direction of their movement, obstaclesin the direction of their movement (such as chairs, desks, tables, beds,televisions, etc.), and generate warnings and courses of movement forthe individual to avoid the obstacles as they move about the home.

At step 645, the navigation feedback is sent (e.g., to smart devices,smart speakers, and so forth). For instance, a smart home controller maytransmit movement instructions to the individual’s mobile device oraudibly present the movement instructions via a speaker associated withthe smart home controller.

Exemplary Method for Generating Personal Articles Insurance Quote

FIG. 7 illustrates a flow diagram of an exemplary method 700 forgenerating a personal articles insurance quote. At block 702, theservers may receive the LIDAR data generated from one or more LIDARcameras 120, such as via wireless communication or data transmissionover one or more radio frequency links and/or via a communicationnetwork. For instance, LIDAR data may be received at a smart homecontroller via a home wireless communication network and a transceiverof the smart home controller.

At block 704, the LIDAR data may be analyzed, via one or more processors(such as at a smart home controller), to determine or identify one ormore personal articles or insurable assets. In some embodiments, theLIDAR data may be analyzed with, or combined with, other sources of datafor enhanced accuracy. For instance, a smart home controller may receivesensor and image data from several sources, such as data from mobiledevices, wearables, smart glasses, smart headgear, home-mounted sensorsand cameras, televisions, etc. that interconnected with a home wirelesscommunication network.

At block 706, in an optional step, the servers may generate anelectronic inventory list of personal belongings including severalpersonal articles (including, e.g., one or more vehicles, and make andmodel thereof) identified from the analysis of the LIDAR data. Theinventory list may also be generated from one or more additional sourcesof data, such as mobile device data and/or images; smart home sensordata and/or images; drone sensor data and/or images; vehicle sensor dataand/or images; and/or smart infrastructure data and/or images. Thegenerated inventory list may further include one or more electronicdevices, televisions, furniture, antiques, paintings, and otherinsurable assets.

At block 708, the servers may generate an electronic personal articlesinsurance quote based upon the one or more personal articles orinsurable assets determined or identified from the LIDAR data. At block710, the server may transmit the electronic personal articles insurancequote and/or inventory list to a mobile device of a customer viawireless communication and/or over one or more radio frequency links fortheir review, modification, and/or approval.

Exemplary Method for Generating an Inventory List of Personal Belongings

FIG. 8 illustrates a flow diagram of an exemplary method 800 forgenerating a personal articles insurance quote. At block 802, theservers may receive the LIDAR data generated from one or more LIDARcameras 120, such as via wireless communication or data transmissionover one or more radio frequency links. At block 804, the LIDAR data maybe analyzed to determine or identify one or more personal articles orinsurable assets.

At block 806, an electronic inventory list of personal belongings may begenerated based upon the one or more personal articles or insurableassets determined or identified from the LIDAR data. The inventory listmay also be generated from one or more additional sources of data, suchas mobile device data and/or images; smart home sensor data and/orimages, including data from one or more sensors or cameras mounted in agarage; drone sensor data and/or images; vehicle sensor data and/orimages; and/or smart infrastructure data and/or images. The generatedinventory list may further include one or more vehicles, electronicdevices, televisions, furniture, antiques, paintings, and so forth.

At block 808, in an optional step, an electronic personal articlesinsurance quote may be generated covering several personal articlesidentified from processor analysis of the LIDAR data and listed withinthe electronic inventory list. At block 810, the electronic inventorylist and/or insurance quote may be transmitted to a mobile device of acustomer via wireless communication and/or over one or more radiofrequency links for customer review, modification, and/or approval.

Exemplary Method for Generating a Homeowners Insurance Quote

FIG. 9 illustrates a flow diagram of an exemplary method for generatinga homeowners insurance quote. At block 902, the servers may receive theLIDAR data generated from one or more LIDAR cameras 120, such as viawireless communication or data transmission over one or more radiofrequency links. For instance, LIDAR data may be received at a smarthome controller via a home wireless communication network and atransceiver of the smart home controller.

In some embodiments, the LIDAR data may be analyzed with, or combinedwith, other sources of data for enhanced accuracy. For instance, a smarthome controller may receive sensor and image data from several sources,such as data from mobile devices, wearables, smart glasses, smartheadgear, home-mounted sensors and cameras, televisions, smart vehicles,etc. that are interconnected with a home wireless communication network.

At block 904, the LIDAR data (either alone in combination with theadditional sources of data) may be analyzed to determine or identify oneor more features or characteristics of a home. The one or more featuresor characteristics of the home determined or identified from the LIDARdata (either alone in combination with the additional sources of data)may include: (1) type of flooring, carpet, or tile; (2) type offixtures; (3) type of cabinets; (4) number and size of bedrooms; (5)number and size of bathrooms; (6) size of garage; (7) type of siding;(8) type of roofing materials; (9) type of windows; and/or (10) numberand/or size of rooms.

At block 906, an electronic homeowners insurance quote may be generatedbased upon, at least in part, the one or more features orcharacteristics of the home determined or identified from the LIDARdata. At block 908, in an optional step, an electronic inventory of homefeatures or characteristics may be generated including several featuresor characteristics identified from processor analysis of the LIDAR data.At block 910, the electronic homeowners insurance quote and/or theelectronic inventory of home features may be transmitted to a mobiledevice of a customer via wireless communication and/or over one or moreradio frequency links for the customer’s review, modification, and/orapproval.

Exemplary Method for Insurance Claim Generation From Lidar Data

FIG. 10 illustrates a flow diagram of an exemplary method for generatingan insurance claim. At block 1002, the servers may receive the LIDARdata generated from one or more LIDAR cameras 120, such as via wirelesscommunication or data transmission over one or more radio frequencylinks. For instance, LIDAR data may be received at a smart homecontroller via a home wireless communication network and a transceiverof the smart home controller.

In some embodiments, the LIDAR data may be analyzed with, or combinedwith, other sources of data for enhanced accuracy. For instance, a smarthome controller may receive sensor and image data from several sources,such as data from mobile devices, wearables, smart glasses, smartheadgear, home-mounted sensors and cameras, televisions, smart vehicles,etc. that are interconnected with a home wireless communication network.

At block 1004, the LIDAR data (either alone or in combination with thedata received from the additional sources mentioned above) may beanalyzed to determine or identify damage to one or more insured assets.The one or more insured assets may be a home, and the damage identifiedfrom processor analysis of the LIDAR data (either alone or incombination with the data received from the additional sources mentionedabove) may be home damage or damage to one or more home features orcharacteristics. The one or more insured assets may include one or morepersonal articles, and the damage identified from processor analysis ofthe LIDAR data (either alone or in combination with the data receivedfrom the additional sources mentioned above) may be home damage ordamage to the one or more personal articles. To further identify thedamage to the one or more insured assets, one or more additional sourcesof data may be analyzed such as such as mobile device data and/orimages; smart home sensor data and/or images; drone sensor data and/orimages; vehicle sensor data and/or images; and/or smart infrastructuredata and/or images.

At block 1006, a proposed electronic insurance claim may be generatedbased upon the damage to the one or more insured assets determined oridentified from the LIDAR data (either alone or in combination with thedata received from the additional sources mentioned above). The proposedelectronic insurance claim may be for customer review, modification,and/or approval.

At block 1008, in an optional step, an electronic inventory list ofpersonal belongings may be generated including several personal articlesidentified from processor analysis of the LIDAR data (either alone or incombination with the data received from the additional sources mentionedabove). At block 1010, in another optional step, repair or replacementcost of one or more insured assets may be estimated from processoranalysis of (i) the LIDAR data, and (ii) one or more additional sourcesof data, such as mobile device data and/or images; smart home sensordata and/or images; drone sensor data and/or images; vehicle sensor dataand/or images; and/or smart infrastructure data and/or images.

At block 1012, the electronic insurance claim and/or electronicinventory list may be transmitted to a mobile device of a customer viawireless communication and/or over one or more radio frequency links forthe customer’s review, modification, and/or approval.

Exemplary Method for Providing First Notice of Loss

FIG. 11 illustrates a flow diagram providing first notice of loss. Atblock 1102, the servers may receive the LIDAR data generated from one ormore LIDAR cameras 120, such as via wireless communication or datatransmission over one or more radio frequency links. At block 1104, theservers may determine that an insurance-related event has occurred basedupon processor analysis of the received LIDAR data and/or additionalsources of data. The additional sources of data may include mobiledevice data and/or images; smart home sensor data and/or images; dronesensor data and/or images; vehicle sensor data and/or images; and/orsmart infrastructure data and/or images.

At block 1106, in response to the determination that theinsurance-related event has occurred, the servers may generate anelectronic first notice of loss. At block 1108, in an optional step, theservers may receive or retrieve one or more additional sources of data,and analyze the received LIDAR and the one or more additional sourcesdata to identify one or more insured assets (e.g., a home and/orpersonal articles) that are damaged. At block 1110, in another optionalstep, the servers may receive or retrieve one or more additional sourcesof data, and analyze the received LIDAR and/or the one or moreadditional sources data to estimate a repair or replacement cost of theidentified one or more insured assets.

Exemplary Method for Navigation for the Vision Impaired

FIG. 12 illustrates a flow diagram for navigation for the visionimpaired. Although the following description refers to servers, itshould be understood that some or all of the steps may be insteadperformed by a mobile computing device or other processing device. Atblock 1202, the servers may receive the LIDAR data generated from one ormore LIDAR cameras 120, such as via wireless communication or datatransmission over one or more radio frequency links. For instance, LIDARdata may be received at a smart home controller via a home wirelesscommunication network and a transceiver of the smart home controller.

In some embodiments, the LIDAR data may be analyzed with, or combinedwith, other sources of data for enhanced accuracy. For instance, a smarthome controller may receive sensor and image data from several sources,such as data from mobile devices, wearables, smart glasses, smartheadgear, home-mounted sensors and cameras, televisions, smart vehicles,etc. that are interconnected with a home wireless communication network.

As noted, in some embodiments, the LIDAR data may be received and/orcollected at a smart home controller and/or a smart infrastructurecontroller. At block 1204, in an optional step, smart home sensor data(including e.g., image data) may be received at the smart homecontroller; and/or smart infrastructure sensor data may be received atthe smart infrastructure controller.

At block 1206, the servers may detect an individual within the LIDARdata (and/or a first location of the individual within the LIDAR data)and one or more obstacles within the LIDAR data (and/or a secondlocation of the one or more obstacles within the LIDAR data). Thedetection may further be based upon the received smart home sensor data,in some embodiments.

At block 1208, in an optional step, the LIDAR data and/or the smart homesensor data may be analyzed to detect a direction of movement of theindividual within or about the home and/or structure. At block 1210, inan optional step, the LIDAR data and/or the smart home sensor data maybe analyzed to generate a virtual map of obstacles within a home and/orstructure.

At block 1212, the LIDAR data and/or the smart home sensor data may beanalyzed to detect (i) the one or more obstacles in front of thedirection of movement of the individual within or about the home and/orstructure, and/or (ii) the second location of the one or more obstaclesin front of the direction of movement of the individual within or aboutthe home and/or structure.

At block 1214, navigation feedback may be generated and provided to thehuman individual to avoid the one or more obstacles and/or move aboutbased upon (i) the first location of the individual, (ii) the directionof movement of the individual, and/or (iii) the second location of theone or more obstacles in front of the direction of movement of theindividual. The navigation feedback may be auditory, and may comprisedirection and distance instructions to guide the individual and avoidthe one or more obstacles. The navigation feedback may also be haptic orvisual (such as bright lights) in some embodiments.

Exemplary Insurance Quote Generation Functionality

In one aspect, a computer-implemented method for generating an insurancequote may be provided. The method may include, via one or more local orremote processors, transceivers, sensors, and/or servers: (1) receivingpreexisting architecture data; (2) creating baseline architecture datausing the preexisting architecture data; (3) receiving LIDAR datagenerated from a LIDAR camera; (4) combining the baseline architecturedata with the LIDAR data to create an architecture profile; and/or (5)generating the insurance quote based upon the architecture profile.

The preexisting architecture data may include a property deed record.The method may further include receiving drone data, and thearchitecture profile may be created further based upon the receiveddrone data.

The method may further include training a machine learning algorithmusing previous architecture data and previous insurance quotes, and theinsurance quote may be generated by inputting the architecture profileinto the trained machine learning algorithm.

The LIDAR data may include 3D point cloud data indicating dimensions ofa room of a house. Additionally or alternatively, the LIDAR data mayinclude data of both an exterior and an interior of a building.

The method may further include using the architecture profile to predicta likelihood of an event, the event comprising one of: a fire event, aflood event, or a wind damage event. The building profile may be aprofile of a house. The method may include additional, less, oralternate actions, including those discussed elsewhere herein.

In another aspect, an electronic device for generating an insurancequote may be provided. The electronic device may be configured to, viaone or more processors, transceivers, and/or sensors: (1) receivepreexisting architecture data; (2) create baseline architecture datausing the preexisting architecture data; (3) receive LIDAR datagenerated from a LIDAR camera; (4) combine the baseline architecturedata with the LIDAR data to create an architecture profile; and (5)generate the insurance quote based upon the architecture profile.

The preexisting architecture data may include a property deed record.The electronic device may further be configured to receive drone data,and create the architecture profile further based upon the receiveddrone data.

The electronic device may further be configured to train a machinelearning algorithm using previous architecture data and previousinsurance quotes, and generate the insurance quote by inputting thearchitecture profile into the trained machine learning algorithm. TheLIDAR data may include 3D point cloud data indicating dimensions of aroom of a house.

The LIDAR data may include data of both an exterior and an interior of abuilding. The electronic device may further be configured to use thearchitecture profile to predict a likelihood of an event. The event mayinclude one of: a fire event, a flood event, or a wind damage event. Theelectronic device may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In another aspect, a computer system for generating an insurance quotemay be provided. The system may include a LIDAR camera, and a memoryconfigured to store non-transitory computer executable instructions andconfigured to interface with a processor. The processor may beconfigured to interface with the memory, and may be further configuredto execute the non-transitory computer executable instructions to causethe processor and/or an associated transceiver to: (1) receivepreexisting architecture data; (2) create baseline architecture datausing the preexisting architecture data; (3) receive LIDAR datagenerated from a LIDAR camera; (4) combine the baseline architecturedata with the LIDAR data to create an architecture profile; and/or (5)generate the insurance quote based upon the architecture profile.

The system may further include a drone configured to gather drone data.The processor may be further configured to execute the non-transitorycomputer executable instructions to cause the processor to create thearchitecture profile further based upon the drone data. The processormay be further configured to execute the non-transitory computerexecutable instructions to cause the processor to: train a machinelearning algorithm using previous architecture data and previousinsurance quotes; and generate the insurance quote by inputting thearchitecture profile into the trained machine learning algorithm.

The LIDAR data may include data of both an exterior and an interior of abuilding. The processor may be further configured to execute thenon-transitory computer executable instructions to cause the processorto use the architecture profile to predict a likelihood of an event. Theevent may include one of: a fire event, a flood event, or a wind damageevent. The computer system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

Exemplary Insurance Claim Generation Functionality

In another aspect, a computer-implemented method for providing firstnotice of loss may be provided. The method may include, via one or morelocal or remote processors, transceivers, sensors, and/or servers: (1)receiving LIDAR data generated from a LIDAR camera; (2) determining thatan event has occurred based upon the received LIDAR data; and/or (3) inresponse to the determination that the event has occurred, generatingand/or providing an electronic or virtual first notice of loss. Thefirst notice of loss may be provided to an insurance provider’s and/oran insured’s computing device. For instance, an electronic first noticeof loss may be transmitted to an insurance provider server or aninsured’s mobile device, and then displayed for review and furtheraction, such as completing, handling, or preparing an insurance claim.The method may include additional, less, or alternate actions, includingthose discussed elsewhere herein.

For instance, the method may further include, via the one or more localor remote processors, transceivers, sensors, and/or servers: (1)receiving smart device data from a smart device, and the determinationthat an event has occurred may be further based upon the received smartdevice data; (2) receiving architecture data including dimensional dataof a building, and the determination that an event has occurred may befurther based upon the received architecture data; and/or (3) receivingdrone data from a drone, and the determination that an event hasoccurred may be further based upon the received drone data. Thedetermination that an event has occurred may be made by using the LIDARdata in conjunction with a machine learning algorithm.

The method may further include training a machine learning algorithmusing previously known dimensional data, and event data, and thedetermination that an event has occurred may be made by inputting theLIDAR data into the machine learning algorithm. The method may furtherinclude: prior to receiving the LIDAR data, sending instructions to auser on how to install the LIDAR camera. The method may further include:determining that a repair to a house has been completed; and in responseto the determination that the repair has been completed, providingnotice that an insurance claim has been satisfied.

In another aspect, an electronic device for providing first notice ofloss may be provided. The electronic device may be configured to, viaone or more processors, transceivers, and/or sensors: (1) receive LIDARdata generated from a LIDAR camera; (2) determine if an event hasoccurred based upon the received LIDAR data; and (3) if the event hasoccurred, generate and provide an electronic or virtual first notice ofloss. The electronic device may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

For instance, the electronic device may be further configured to receivesmart device data from a smart device, and determine if the event hasoccurred further based upon the received smart device data. Theelectronic device may be further configured to: receive architecturedata including dimensional data of a building; and determine if theevent has occurred further based upon the received architecture data.The electronic device may be further configured to: receive drone data;and determine if the event has occurred further based upon the receiveddrone data. The electronic device may be further configured to: train amachine learning algorithm using previously known dimensional data, andevent data; and determine if the event has occurred by inputting theLIDAR data into the machine learning algorithm. The electronic devicemay be further configured to provide an offer to discount an insurancepolicy if the user agrees to set up the LIDAR camera in a house of theuser.

In another aspect, a computer system for providing first notice of lossmay be provided. The system may include: a LIDAR camera, and a memoryconfigured to store non-transitory computer executable instructions andconfigured to interface with a processor. The processor may beconfigured to interface with the memory, and further configured toexecute the non-transitory computer executable instructions to cause theprocessor and/or an associated transceiver to: (1) receive LIDAR datagenerated from the LIDAR camera; (2) determine if an event has occurredbased upon the received LIDAR data; and (3) if the event has occurred,generate and provide an electronic or virtual first notice of loss. Thesystem may include additional, less, or alternate functionality,including that discussed elsewhere herein.

For instance, the system may further include a smart device configuredto gather smart device data. The processor may be further configured toexecute the non-transitory computer executable instructions to cause theprocessor to determine if the event has occurred further based upon thesmart device data.

The system may further include a drone configured to gather drone data.The processor may be further configured to execute the non-transitorycomputer executable instructions to cause the processor to determine ifthe event has occurred further based upon the drone data.

The processor may further be configured to execute the non-transitorycomputer executable instructions to cause the processor to: train amachine learning algorithm using previously known dimensional data, andevent data; and determine if the event has occurred by inputting theLIDAR data into the machine learning algorithm.

The processor may be further configured to execute the non-transitorycomputer executable instructions to cause the processor to: prior toreceiving the LIDAR data, cause a display device to display instructionsto a user on how to install the LIDAR camera. The processor may furtherbe configured to execute the non-transitory computer executableinstructions to cause the processor to provide an offer to discount aninsurance policy if the user agrees to set up the LIDAR camera in ahouse of the user.

The electronic first notice of loss generated may be provided to aninsurance provider’s and/or an insured’s computing device. For instance,an electronic first notice of loss may be transmitted to an insuranceprovider server or an insured’s mobile device, and then displayed forreview and further action, such as completing, preparing, processing, orhandling an insurance claim.

Exemplary Assistance to an Impaired Individual Functionality

In another aspect, a computer-implemented method for assisting a humanindividual may be provided. The method may include, via one or morelocal or remote processors, transceivers, sensors, and/or servers: (1)receiving LIDAR data generated from a LIDAR camera; and/or (2)generating and providing navigation feedback to the human individualbased upon the LIDAR data.

The navigation feedback may be auditory, and may include direction anddistance instructions to guide the human individual. The navigationfeedback may further be delivered to the human individual through asmart speaker positioned in a home.

The method may further include receiving global positioning system (GPS)data of the human individual, and the provided navigation feedback mayfurther be based upon the GPS data of the human individual. The LIDARcamera may be a first LIDAR camera, and the LIDAR data may be firstLIDAR data. And, the method may further include receiving second LIDARdata generated from a second LIDAR camera. The second LIDAR camera maybe configured to be stationed in a home, and the provided navigationfeedback may further be based upon the second LIDAR data.

The method may further include receiving drone data, and the providednavigation feedback may further be based upon the drone data. The methodmay further include: based upon the LIDAR data, determining that thehuman individual is on course to enter a crosswalk; based upon the LIDARdata, determining that an object is approaching the crosswalk; and inresponse to both (i) the determination that the human individual is onthe course to enter the crosswalk, and (ii) the determination that theobject is approaching the crosswalk, providing feedback to the humanindividual instructing the human individual not to enter the crosswalk.

The method may further include: prior to gathering the LIDAR data,creating a layout of a home including at least one 3D point cloud map.The provided navigation feedback may be generated by combining thelayout of the home with the LIDAR data. The method may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

In another aspect an electronic device for assisting a human individualmay be provided. The electronic device may be configured to, via one ormore processors, transceivers, and/or sensors: (1) receive LIDAR datagenerated from the LIDAR camera; and/or (2) generate and providenavigation feedback to the human individual based upon the LIDAR data.

The navigation feedback may be auditory, and may include direction anddistance instructions to guide the human individual. The electronicdevice may be further configured to deliver the feedback to the humanindividual through a smart speaker positioned in a home.

The electronic device may be further configured to: receive globalpositioning system (GPS) data from a GPS device; and provide thenavigation feedback further based upon the GPS data.

The LIDAR camera may be a first LIDAR camera, and the LIDAR data may befirst LIDAR data. The electronic device may be further configured to:receive second LIDAR data generated from a second LIDAR camera. Thesecond LIDAR camera may be configured to be stationed in a home. And,the electronic device may be further configured to provide thenavigation feedback further based upon the second LIDAR data. Theelectronic device may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In another aspect, a computer system for assisting a human individualmay be provided. The system may include: (a) a LIDAR camera configuredto be harnessed to a human individual, and (b) a memory configured tostore non-transitory computer executable instructions and configured tointerface with a processor. The processor may be configured to interfacewith the memory, and may be further configured to execute thenon-transitory computer executable instructions to cause the processorand/or an associated transceiver to: (1) receive LIDAR data generatedfrom the LIDAR camera; and/or (2) generate and provide navigationfeedback to the human individual based upon the LIDAR data.

The navigation feedback may be auditory, and may include direction anddistance instructions to guide the human individual. The system mayfurther include a smart speaker configured to be positioned in a home.The processor may be further configured to execute the non-transitorycomputer executable instructions to cause the processor to deliver: (i)the navigation feedback as auditory feedback, and (ii) the navigationfeedback through the smart speaker.

The system may further include a device configured to: (i) gather globalpositioning system (GPS) data, and (ii) be attached to the LIDAR camera.The provided navigation feedback may be further based upon the GPS data.

The LIDAR camera may be a first LIDAR camera, and the LIDAR data may befirst LIDAR data. The system may further include a second LIDAR camera.The second LIDAR camera may be configured to be stationed in a home. Theprocessor may be further configured to execute the non-transitorycomputer executable instructions to cause the processor to provide thenavigation feedback to the human individual based further on the secondLIDAR data.

The system may further include a drone configured to gather drone data.The processor may be further configured to execute the non-transitorycomputer executable instructions to cause the processor to provide thenavigation feedback to the human individual based further on the dronedata.

The processor may be further configured to execute the non-transitorycomputer executable instructions to cause the processor to: based uponthe LIDAR data, determine if the human individual is on course to entera crosswalk; based upon the LIDAR data, determine if an object isapproaching the crosswalk; and if both (i) the human individual is onthe course to enter the crosswalk, and (ii) the object is approachingthe crosswalk, provide feedback to the human individual instructing thehuman individual not to enter the crosswalk. The computer system mayinclude additional, less, or alternate functionality, including thatdiscussed elsewhere herein.

Generating Personal Articles Insurance Quote

In one aspect, a computer-implemented method for generating a personalarticles insurance quote may be provided. The method may include, viaone or more processors, transceivers, sensors, and/or servers: (1)receiving light detection and ranging (LIDAR) data generated from one ormore LIDAR cameras; (2) analyzing the LIDAR data to determine oridentify one or more personal articles or insurable assets; and/or (3)generating an electronic personal articles insurance quote based uponthe one or more personal articles or insurable assets determined oridentified from the LIDAR data. The method may include additional, less,or alternate functionality, including that discussed elsewhere herein.

For instance, the method may include, via the one or more processors,transceivers, sensors, and/or servers, transmitting the electronicpersonal articles insurance quote to a mobile device of a customer viawireless communication and/or data transmission over one or more radiofrequency links for the customer’s review, modification, and/orapproval.

The method may also include, via the one or more processors,transceivers, sensors, and/or servers, generating an electronicinventory list of personal belongings including several personalarticles identified from processor analysis of the LIDAR data, andtransmitting the electronic inventory list to a mobile device of acustomer via wireless communication and/or data transmission over one ormore radio frequency links for customer review, modification, and/orapproval.

The method may include, via the one or more processors, transceivers,sensors, and/or servers, generating an electronic inventory list ofpersonal belongings including several personal articles identified fromprocessor analysis of (i) the LIDAR data, and (ii) one or moreadditional sources of data, the one or more additional sources of dataincluding at least one of mobile device data and/or images; smart homesensor data and/or images; drone sensor data and/or images; vehiclesensor data and/or images; and/or smart infrastructure data and/orimages. The electronic inventory list may include one or more vehicles,and make and model thereof. Additionally or alternatively, theelectronic inventory list may include one or more electronic devices,televisions, furniture, antiques, paintings, etc. The LIDAR data may bereceived via wireless communication or data transmission over one ormore radio frequency links.

In another aspect, a computer system configured to generate anelectronic personal articles insurance quote may be provided. Thecomputer system may include one or more processors, transceivers,sensors, and/or servers configured to: (1) receive light detection andranging (LIDAR) data generated from one or more LIDAR cameras; (2)analyze the LIDAR data to determine or identify one or more personalarticles or insurable assets; (3) generate an electronic personalarticles insurance quote based upon the one or more personal articles orinsurable assets determined or identified from the LIDAR data; and/or(4) transmit the electronic personal articles insurance quote to amobile device of a customer via wireless communication and/or datatransmission over one or more radio frequency links for their review,modification, and/or approval.

The system may also be configured to, via the one or more processors,transceivers, sensors, and/or servers, (5) generate an electronicinventory list of personal belongings including several personalarticles identified from processor analysis of (i) the LIDAR data, and(ii) one or more additional sources of data, the or more additionalsources of data including at least one of: mobile device data and/orimages; smart home sensor data and/or images; drone sensor data and/orimages; vehicle sensor data and/or images; and/or smart infrastructuredata and/or images, and (6) transmit the electronic inventory list to amobile device of a customer via wireless communication and/or datatransmission over one or more radio frequency links for their review,modification, and/or approval. The system may also be configured to, viathe one or more processors, transceivers, sensors, and/or servers,receive the LIDAR data via wireless communication or data transmissionover one or more radio frequency links. The system may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

In yet another aspect, a computer system for generating an electronicpersonal articles insurance quote may be provided. The computer systemmay include: one or more processors; and a program memory coupled to theone or more processors and storing executable instructions that whenexecuted by the one or more processors cause the computer system to: (1)receive light detection and ranging (LIDAR) data generated from one ormore LIDAR cameras; (2) analyze the LIDAR data to determine or identifyone or more personal articles or insurable assets; and (3) generate anelectronic personal articles insurance quote based upon the one or morepersonal articles or insurable assets determined or identified from theLIDAR data.

In the computer system, the executable instructions may further causethe computer system to transmit the electronic personal articlesinsurance quote to a mobile device of a customer via wirelesscommunication and/or data transmission over one or more radio frequencylinks for customer review, modification, and/or approval. The executableinstructions may further cause the computer system to generate anelectronic inventory list of personal belongings including severalpersonal articles identified from processor analysis of the LIDAR data.

The executable instructions may further cause the computer system togenerate an electronic inventory list of personal belongings includingseveral personal articles identified from processor analysis of (i) theLIDAR data, and (ii) one or more additional sources of data, the one ormore additional sources of data including at least one of: mobile devicedata and/or images; smart home sensor data and/or images; drone sensordata and/or images; vehicle sensor data and/or images; and/or smartinfrastructure data and/or images.

Generating Inventory List of Personal Belongings

In one aspect, a computer-implemented method for generating anelectronic inventory list of personal belongings may be provided. Themethod may include, via one or more processors, transceivers, sensors,and/or servers: (1) receiving light detection and ranging (LIDAR) datagenerated from one or more LIDAR cameras; (2) analyzing the LIDAR datato determine or identify one or more personal articles or insurableassets; (3) generating an electronic inventory list of personalbelongings based upon the one or more personal articles or insurableassets determined or identified from the LIDAR data; and/or (4)transmitting the electronic inventory list to a mobile device of acustomer via wireless communication and/or data transmission over one ormore radio frequency links for customer review, modification, and/orapproval. The method may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

For instance, the method may include, via the one or more processors,transceivers, sensors, and/or servers, generating an electronic personalarticles insurance quote covering several personal articles identifiedfrom processor analysis of the LIDAR data and listed within theelectronic inventory list, and/or transmitting the electronic personalarticles insurance quote to a mobile device of a customer via wirelesscommunication and/or data transmission over one or more radio frequencylinks for the customer’s review, modification, and/or approval.

The method may include generating the electronic inventory list, via theone or more processors, transceivers, sensors, and/or servers, byprocessor analysis of (i) the LIDAR data, and (ii) one or moreadditional sources of data, the one or more additional sources of dataincluding at least one of: mobile device data and/or images; smart homesensor data and/or images; drone sensor data and/or images; vehiclesensor data and/or images; and/or smart infrastructure data and/orimages. The electronic inventory list may include one or more vehicles,and make and model thereof. The electronic inventory list may includeone or more electronic devices, televisions, furniture, antiques,paintings, jewelry, or other insurable belongings. The LIDAR data may bereceived via wireless communication or data transmission over one ormore radio frequency links.

In another aspect, a computer system configured to generate anelectronic inventory list of personal belongings may be provided. Thecomputer system may include one or more processors, transceivers,sensors, and/or servers configured to: (1) receive light detection andranging (LIDAR) data generated from one or more LIDAR cameras; (2)analyze the LIDAR data to determine or identify one or more personalarticles or insurable assets; (3) generate an electronic inventory listof personal belongings based upon the one or more personal articles orinsurable assets determined or identified from the LIDAR data; and/or(4) transmit the electronic inventory list to a mobile device of acustomer via wireless communication and/or data transmission over one ormore radio frequency links for customer review, modification, and/orapproval. The computer system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

For instance, the system may be further configured to, via the one ormore processors, transceivers, sensors, and/or servers, generate anelectronic personal articles insurance quote covering several personalarticles identified from processor analysis of the LIDAR data andincluding personal articles listed in the electronic inventory list. Thecomputer system may be further configured to, via the one or moreprocessors, transceivers, sensors, and/or servers, transmit theelectronic personal articles insurance quote to a mobile device of acustomer via wireless communication and/or data transmission over one ormore radio frequency links for customer review, modification, and/orapproval.

In the computer system, the generation of the electronic inventory listmay include, via the one or more processors, transceivers, sensors,and/or servers, processor analysis of (i) the LIDAR data, and (ii) oneor more additional sources of data, the additional sources of dataincluding at least one of: mobile device data and/or images; smart homesensor data and/or images; drone sensor data and/or images; vehiclesensor data and/or images; and/or smart infrastructure data and/orimages.

In the computer system, the electronic inventory list may include one ormore vehicles, and make and model thereof. The electronic inventory listmay include one or more electronic devices, televisions, furniture,antiques, and/or paintings. The computer system may be furtherconfigured to, via the one or more processors, transceivers, sensors,and/or servers, receive the LIDAR data via wireless communication ordata transmission over one or more radio frequency links.

In yet another aspect, a computer system for generating an electronicpersonal articles insurance quote may be provided. The computer systemmay include: one or more processors; and a program memory coupled to theone or more processors and storing executable instructions that whenexecuted by the one or more processors cause the computer system to: (1)receive light detection and ranging (LIDAR) data generated from one ormore LIDAR cameras; (2) analyze the LIDAR data to determine or identifyone or more personal articles or insurable assets; and (3) generate anelectronic inventory list of personal belongings based upon the one ormore personal articles or insurable assets determined or identified fromthe LIDAR data. The system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In the computer system, the executable instructions may further causethe computer system to transmit the electronic inventory list to amobile device of a customer via wireless communication and/or datatransmission over one or more radio frequency links for customer review,modification, and/or approval. The executable instructions may furthercause the computer system to generate an electronic personal articlesinsurance quote covering several personal articles identified fromprocessor analysis of the LIDAR data and including personal articleslisted in the electronic inventory list. The executable instructions mayfurther cause the computer system to transmit the electronic personalarticles insurance quote to a mobile device of a customer via wirelesscommunication and/or data transmission over one or more radio frequencylinks for customer review, modification, and/or approval.

Generating Homeowners Insurance Quote

In one aspect, a computer-implemented method of generating an electronichomeowners insurance quote may be provided. The method may include, viaone or more processors, transceivers, sensors, and/or servers: (1)receiving light detection and ranging (LIDAR) data generated from one ormore LIDAR cameras; (2) analyzing the LIDAR data to determine oridentify one or more features or characteristics of a home; (3)generating an electronic homeowners insurance quote based upon, at leastin part, the one or more features or characteristics of the homedetermined or identified from the LIDAR data; and/or (4) transmittingthe electronic homeowners insurance quote to a mobile device of acustomer via wireless communication and/or data transmission over one ormore radio frequency links for the customer’s review, modification,and/or approval. The method may include additional, less, or alternateactions, including those discussed elsewhere herein.

The method may include, via the one or more processors, transceivers,sensors, and/or servers, generating an electronic inventory of homefeatures or characteristics including several features orcharacteristics identified from processor analysis of the LIDAR data.Additionally or alternatively, the method may include, via the one ormore processors, transceivers, sensors, and/or servers, generating anelectronic inventory of home features or characteristics includingseveral features or characteristics identified from processor analysisof (i) the LIDAR data, and (ii) one or more additional sources of data,the one or more additional sources of data including at least one of:mobile device data and/or images; smart home sensor data and/or images;drone sensor data and/or images; vehicle sensor data and/or images;and/or smart infrastructure data and images.

The one or more features or characteristics of the home determined oridentified from the LIDAR data may include: (1) type of flooring,carpet, or tile; (2) type of fixtures; (3) type of cabinets; (4) numberand size of bedrooms; (5) number and size of bathrooms; (6) size ofgarage; (7) type of siding; (8) type of roofing materials; (9) type ofwindows; and/or (10) number and size of rooms.

The LIDAR data may be received via wireless communication or datatransmission over one or more radio frequency links.

In another aspect, a computer system configured to generate a homeownersinsurance quote may be provided. The system may include one or moreprocessors, transceivers, sensors, and/or servers configured to: (1)receive light detection and ranging (LIDAR) data generated from one ormore LIDAR cameras, such as via wireless communication or datatransmission over one or more radio frequency links; (2) analyze theLIDAR data to determine or identify one or more features orcharacteristics of a home; (3) generate an electronic homeownersinsurance quote based upon, at least in part, the one or more featuresor characteristics of the home determined or identified from the LIDARdata; and/or (4) transmit the electronic homeowners or renters insurancequote to a mobile device of a customer via wireless communication and/ordata transmission over one or more radio frequency links for customerreview, modification, and/or approval. The computer system may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

For instance, the computer system may be configured to, via the one ormore processors, transceivers, sensors, and/or servers, generate aninventory of home features or characteristics including several featuresor characteristics identified from processor analysis of (i) the LIDARdata, and (ii) one or more additional sources of data, the additionalsources of data including at least one of: mobile device data and/orimages; smart home sensor data and/or images; drone sensor data and/orimages; vehicle sensor data and/or images; and/or smart infrastructuredata and images.

The one or more features or characteristics of the home determined oridentified from the LIDAR data may include: (1) type of flooring,carpet, or tile; (2) type of fixtures; (3) type of cabinets; (4) numberand size of bedrooms; (5) number and size of bathrooms; (6) size ofgarage; (7) type of siding; (8) type of roofing materials; and/or (9)type of windows.

The one or more features or characteristics of the home determined oridentified from the LIDAR data may include number and size of rooms. TheLIDAR data may be received via wireless communication or datatransmission over one or more radio frequency links.

In yet another aspect, a computer system configured to generate ahomeowners insurance quote may be provided. The computer system mayinclude: one or more processors; and a program memory coupled to the oneor more processors and storing executable instructions that whenexecuted by the one or more processors cause the computer system to: (1)receive light detection and ranging (LIDAR) data generated from one ormore LIDAR cameras; (2) analyze the LIDAR data to determine or identifyone or more features or characteristics of a home; and (3) generate anelectronic homeowners insurance quote based upon, at least in part, theone or more features or characteristics of the home determined oridentified from the LIDAR data. The computer system may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

For instance, the executable instructions may further cause the computersystem to transmit the electronic homeowners or renters insurance quoteto a mobile device of a customer via wireless communication and/or datatransmission over one or more radio frequency links for customer review,modification, and/or approval. The executable instructions may furthercause the computer system to generate an electronic inventory of homefeatures or characteristics including several features orcharacteristics identified from processor analysis of the LIDAR data.

The executable instructions may further cause the computer system togenerate an inventory of home features or characteristics includingseveral features or characteristics identified from processor analysisof (i) the LIDAR data, and (ii) one or more additional sources of data,the one or more additional sources of data including at least one of:mobile device data and/or images; smart home sensor data and/or images;drone sensor data and/or images; vehicle sensor data and/or images;and/or smart infrastructure data and images.

The one or more features or characteristics of the home determined oridentified from the LIDAR data may include: (1) type of flooring,carpet, or tile; (2) type of fixtures; (3) type of cabinets; (4) numberand size of bedrooms; (5) number and size of bathrooms; (6) size ofgarage; (7) type of siding; (8) type of roofing materials; and (9) typeof windows.

The one or more features or characteristics of the home determined oridentified from the LIDAR data may include number and size of rooms.

Generating Claim for Customer Review From Lidar Data

In one aspect, a computer-implemented method for generating anelectronic insurance claim may be provided. The method may include, viaone or more processors, transceivers, sensors, and/or servers: (1)receiving light detection and ranging (LIDAR) data generated from one ormore LIDAR cameras; (2) analyzing the LIDAR data to determine oridentify damage to one or more insured assets; (3) generating anelectronic insurance claim based upon the damage to the one or moreinsured assets determined or identified from the LIDAR data; and/or (4)transmitting the electronic insurance claim to a mobile device of acustomer via wireless communication and/or data transmission over one ormore radio frequency links for the customer’s review, modification,and/or approval. The method may include additional, less, or alternateactions, including those discussed elsewhere herein.

For instance, the one or more insured assets may be a home, and thedamage identified from processor analysis of the LIDAR data may be homedamage or damage to one or more home features or characteristics.Additionally or alternatively, the one or more insured assets mayinclude one or more personal articles, and the damage identified fromprocessor analysis of the LIDAR data may be home damage or damage to theone or more personal articles.

The method may include, via the one or more processors, transceivers,sensors, and/or servers, generating an electronic inventory list ofpersonal belongings including several personal articles identified fromprocessor analysis of the LIDAR data, and transmitting the electronicinventory list to a mobile device of a customer via wirelesscommunication and/or data transmission over one or more radio frequencylinks for customer review, modification, and/or approval.

The method may include, via the one or more processors, transceivers,sensors, and/or servers, determining or identifying damage to one ormore insured assets from processor analysis of (i) the LIDAR data, and(ii) one or more additional sources of data, the one or more additionalsources of data including at least one of: mobile device data and/orimages; smart home sensor data and/or images; drone sensor data and/orimages; vehicle sensor data and/or images; and/or smart infrastructuredata and/or images.

The method may include, via the one or more processors, transceivers,sensors, and/or servers, estimating repair or replacement cost of one ormore insured assets from processor analysis of (i) the LIDAR data, and(ii) one or more additional sources of data, the one or more additionalsources of data including at least one of: mobile device data and/orimages; smart home sensor data and/or images; drone sensor data and/orimages; vehicle sensor data and/or images; and/or smart infrastructuredata and/or images.

The LIDAR data may be received via wireless communication or datatransmission over one or more radio frequency links.

In another aspect, a computer system configured to generate anelectronic insurance claim may be provided. The system may include oneor more processors, transceivers, sensors, and/or servers configured to:(1) receive light detection and ranging (LIDAR) data generated from oneor more LIDAR cameras; (2) analyze the LIDAR data to determine oridentify damage to one or more insured assets; (3) generate anelectronic insurance claim based upon the damage to the one or moreinsured assets determined or identified from the LIDAR data; and/or (4)transmit the electronic insurance claim to a mobile device of a customervia wireless communication and/or data transmission over one or moreradio frequency links for the customer’s review, modification, and/orapproval. The computer system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

For instance, the system may further be configured to, via the one ormore processors, transceivers, sensors, and/or servers, transmit theelectronic insurance claim to a mobile device of a customer via wirelesscommunication and/or data transmission over one or more radio frequencylinks for the customer’s review, modification, and/or approval.

The one or more insured assets may be a home, and the damage identifiedfrom processor analysis of the LIDAR data may be home damage or damageto one or more home features or characteristics. The one or more insuredassets may include one or more personal articles, and the damageidentified from processor analysis of the LIDAR data may be home damageor damage to the one or more personal articles.

The computer system may further be configured to, via the one or moreprocessors, transceivers, sensors, and/or servers, generate anelectronic inventory list of personal belongings including severalpersonal articles identified from processor analysis of the LIDAR data.The computer system may further be configured to, via the one or moreprocessors, transceivers, sensors, and/or servers, transmit theelectronic inventory list to a mobile device of a customer via wirelesscommunication and/or data transmission over one or more radio frequencylinks for customer review, modification, and/or approval.

The system may be configured to, via the one or more processors,transceivers, sensors, and/or servers, determine or identify damage toone or more insured assets from processor analysis of (i) the LIDARdata, and (ii) one or more additional sources of data, the one or moreadditional sources of data including at least one of: mobile device dataand/or images; smart home sensor data and/or images; drone sensor dataand/or images; vehicle sensor data and/or images; and/or smartinfrastructure data and/or images. Additionally or alternatively, thesystem may be configured to, via the one or more processors,transceivers, sensors, and/or servers, estimate repair or replacementcost of one or more insured assets from processor analysis of (i) theLIDAR data, and (ii) one or more additional sources of data, the one ormore additional sources of data including at least one of: mobile devicedata and/or images; smart home sensor data and/or images; drone sensordata and/or images; vehicle sensor data and/or images; and/or smartinfrastructure data and/or images.

The system may further be configured to, via the one or more processors,transceivers, sensors, and/or servers, receive the LIDAR data viawireless communication or data transmission over one or more radiofrequency links.

In yet another aspect, a computer system for generating an electronicinsurance claim may be provided. The system may include: one or moreprocessors; and a program memory coupled to the one or more processorsand storing executable instructions that when executed by the one ormore processors cause the computer system to: (1) receive lightdetection and ranging (LIDAR) data generated from one or more LIDARcameras; (2) analyze the LIDAR data to determine or identify damage toone or more insured assets; and (3) generate an electronic insuranceclaim based upon the damage to the one or more insured assets determinedor identified from the LIDAR data. The computer system may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

For instance, the executable instructions may further cause the computersystem to transmit the electronic insurance claim to a mobile device ofa customer via wireless communication and/or data transmission over oneor more radio frequency links for the customer’s review, modification,and/or approval.

First Notice of Loss

In one aspect, a computer-implemented method for providing first noticeof loss may be provided. The method may include, via one or moreprocessors, transceivers, sensors, and/or servers: (1) receiving lightdetection and ranging (LIDAR) data generated from a LIDAR camera; (2)determining that an insurance-related event has occurred based uponprocessor analysis of the received LIDAR data; (3) in response to thedetermination that the insurance-related event has occurred, generatingan electronic first notice of loss; and/or (4) transmitting theelectronic first notice of loss to one or more local or remote computingdevices, such as an insured’s mobile device, or otherwise displaying theelectronic first notice of loss on one or more local or remote computingdevice display screens. The method may include additional, less, oralternate actions, including those discussed elsewhere herein.

For instance, the method may include, via the one or more processors,transceivers, sensors, and/or servers, receiving or retrieving one ormore additional sources of data, and analyzing the received LIDAR andthe one or more additional sources data to determine that theinsurance-related event has occurred. The one or more additional sourcesof data may include: mobile device data and/or images; smart home sensordata and/or images; drone sensor data and/or images; vehicle sensor dataand/or images; and/or smart infrastructure data and/or images.

The method may include, via the one or more processors, transceivers,sensors, and/or servers, receiving or retrieving one or more additionalsources of data, and analyzing the received LIDAR and the one or moreadditional sources data to identify one or more insured assets that aredamaged. Additionally or alternatively, the method may include, via theone or more processors, transceivers, sensors, and/or servers, receivingor retrieving one or more additional sources of data, and analyzing thereceived LIDAR and the one or more additional sources data to estimatean amount of damage to the identified one or more insured assets, and/orto estimate a repair or replacement cost of the identified one or moreinsured assets. The identified one or more insured assets may include ahome, vehicles, and/or personal articles.

The LIDAR data may be received via wireless communication or datatransmission over one or more radio frequency links.

In another aspect, a computer system configured to provide first noticeof loss may be provided. The method may include, via one or moreprocessors, transceivers, sensors, and/or servers: (1) receive lightdetection and ranging (LIDAR) data generated from a LIDAR camera, suchas via wireless communication or data transmission over one or moreradio frequency links; (2) determine that an insurance-related event hasoccurred based upon processor analysis of the received LIDAR data; (3)in response to the determination that the insurance-related event hasoccurred, generate an electronic first notice of loss; and/or (4)display the electronic first notice of loss on one or more local orremote display screens of computing devices, and/or transmit theelectronic first notice of loss to one or more local or remote computingdevices, such as an insured’s mobile device, for display. The system mayinclude additional, less, or alternate functionality, including thatdiscussed elsewhere herein.

For instance, the system may be configured to, via the one or moreprocessors, transceivers, sensors, and/or servers, receive or retrieveone or more additional sources of data, and analyzing the received LIDARand the one or more additional sources data to determine that theinsurance-related event has occurred. The one or more additional sourcesof data include: mobile device data and/or images; smart home sensordata and/or images; drone sensor data and/or images; vehicle sensor dataand/or images; and/or smart infrastructure data and/or images.

The system may be configured to, via the one or more processors,transceivers, sensors, and/or servers, receive or retrieve one or moreadditional sources of data, and analyzing the received LIDAR and the oneor more additional sources data to identify one or more insured assetsthat are damaged, and/or to estimate an amount of damage to theidentified one or more insured assets or estimate a repair orreplacement cost of the identified one or more insured assets.

The identified one or more insured assets may include a home, vehicles,and/or personal articles. The one or more processors, transceivers,sensors, and/or servers, may be configured to receive the LIDAR data viawireless communication or data transmission over one or more radiofrequency links.

In yet another aspect, a computer system configured to provide firstnotice of loss may be provided. The computer system may include: one ormore processors; and a program memory coupled to the one or moreprocessors and storing executable instructions that when executed by theone or more processors cause the computer system to: (1) receive lightdetection and ranging (LIDAR) data generated from a LIDAR camera; (2)determine if an insurance-related event has occurred based uponprocessor analysis of the received LIDAR data; and (3) if theinsurance-related event has occurred, generate an electronic firstnotice of loss. The system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

For instance, the executable instructions may further cause the computersystem to receive or retrieve one or more additional sources of data,and analyzing the received LIDAR and the one or more additional sourcesdata to determine that the insurance-related event has occurred.

Navigation for Vision-Impaired

In one aspect, a computer-implemented method for assisting a humanindividual or for providing navigation assistance for vision-impairedindividuals may be provided. The method may include, via one or moreprocessors, sensors, servers, and/or transceivers: (1) receiving lightdetection and ranging (LIDAR) data generated from a LIDAR camera; (2)detecting, within the LIDAR data: (i) the human individual, (ii) a firstlocation of the human individual, (iii) one or more obstacles, and (iv)a second location of the one or more obstacles; and/or (3) providingnavigation feedback to the human individual based upon the LIDAR data,the first location of the individual, and/or the second location of theone or more obstacles as determined from the LIDAR data to facilitateproviding navigation assistance to vision-impaired individuals. Thenavigation feedback may be auditory or visual, and may include directionand distance instructions to guide the individual and avoid the one ormore obstacles. The method may include additional, less, or alternateactions, including that discussed elsewhere herein.

For instance, the method may include, via the one or more processors,sensors, servers, and/or transceivers: (1) receiving the LIDAR data at asmart home controller; (2) receiving, at the smart home controller,smart home sensor data including image data; (3) analyzing the LIDARdata and/or the smart home sensor data to detect the individual or thefirst location of the individual within or about a home; (4) analyzingthe LIDAR data and/or the smart home sensor data to detect a directionof movement of the individual within or about the home; (5) analyzingthe LIDAR data and/or the smart home sensor data to detect (i) the oneor more obstacles in front of the direction of movement of theindividual within or about the home, and/or (ii) the second location ofthe one or more obstacles in front of the direction of movement of theindividual within or about the home; and (6) generating and providingnavigation feedback to the individual to avoid the one or more obstaclesand/or move about the home based upon (i) the first location of theindividual, (ii) the direction of movement of the individual, and/or(iii) the second location of the one or more obstacles in front of thedirection of movement of the individual.

The method may include, via the one or more processors, sensors,servers, and/or transceivers: receiving the LIDAR data at a smart homecontroller; receiving, at the smart controller, smart home sensor dataincluding image data; and analyzing the LIDAR data and/or the smart homesensor data to generate a virtual map of obstacles within a home.

The method may include, via the one or more processors, sensors,servers, and/or transceivers: receiving the LIDAR data at a mobiledevice of the individual; and generating the navigation feedback via themobile device.

The method may include, via the one or more processors, sensors,servers, and/or transceivers: (1) receiving the LIDAR data at a smartinfrastructure controller; (2) receiving, at the smart infrastructurecontroller, smart infrastructure sensor data (including image data) atthe smart infrastructure controller; (3) analyzing the LIDAR data and/orthe smart infrastructure sensor data to detect the individual or thefirst location of the individual; (4) analyzing the LIDAR data and/orthe smart infrastructure sensor data to detect a direction of movementof the individual; (5) analyzing the LIDAR data and/or the smartinfrastructure sensor data to detect (i) the one or more obstacles infront of the direction of movement of the individual, and/or (ii) thesecond location of the one or more obstacles in front of the directionof movement of the individual; and/or (6) providing navigation feedbackto the individual to avoid the one or more obstacles and/or move aboutbased upon (i) the first location of the individual, (ii) the directionof movement of the individual, and/or (iii) the second location of theone or more obstacles in front of the direction of movement of theindividual.

The LIDAR data may be received via wireless communication or datatransmission over one or more radio frequency links.

In another aspect, a computer system configured to assist a humanindividual or provide navigation assistance for vision-impairedindividuals may be provided. The computer system may include one or moreprocessors, sensors, servers, and/or transceivers configured to: (1)receive light detection and ranging (LIDAR) data generated from a LIDARcamera; (2) detect, within the LIDAR data: (i) the human individual,(ii) a first location of the human individual, (iii) one or moreobstacles, and (iv) a second location of the one or more obstacles; and(3) provide navigation feedback to the human individual based upon theLIDAR data, the first location of the individual, and/or the secondlocation of the one or more obstacles as determined from the LIDAR datato facilitate providing navigation assistance to the human individual.The navigation feedback may be visual or auditory, and may includedirection and distance instructions to guide the individual and avoidthe one or more obstacles. The computer system may include additional,less, or alternate functionality, including that discussed elsewhereherein.

For instance, the computer system may include, via the one or moreprocessors, sensors, servers, and/or transceivers, to: (a) receive theLIDAR data at a smart home controller receive, at the smart homecontroller, smart home sensor data including image data; (b) receive, atthe smart home controller, smart home sensor data including image data;(c) analyze the LIDAR data and/or the smart home sensor data to detectthe individual or the first location of the individual within or about ahome; (d) analyze the LIDAR data and/or the smart home sensor data todetect a direction of movement of the individual within or about thehome; (e) analyze the LIDAR data and/or the smart home sensor data todetect (i) the one or more obstacles in front of the direction ofmovement of the individual within or about the home, and/or (ii) thesecond location of the one or more obstacles in front of the directionof movement of the individual within or about the home; and (f) generateand provide navigation feedback to the individual to avoid the one ormore obstacles and/or move about the home based upon (i) the firstlocation of the individual, (ii) the direction of movement of theindividual, and/or (iii) the second location of the one or moreobstacles in front of the direction of movement of the individual.

The computer system may be further configured to, via the one or moreprocessors, sensors, servers, and/or transceivers: receive the LIDARdata at a smart home controller; receive, at the smart controller, smarthome sensor data including image data; and analyze the LIDAR data and/orthe smart home sensor data to generate a virtual map of obstacles withina home.

The computer system may be further configured to, via the one or moreprocessors, sensors, servers, and/or transceivers, to: receive the LIDARdata at a mobile device of the individual; and/or generate thenavigation feedback via the mobile device.

The computer system may be further configured to, via the one or moreprocessors, sensors, servers, and/or transceivers, to: receive the LIDARdata at a smart infrastructure controller, such as via wirelesscommunication or data transmission over one or more radio frequencylinks; receive smart infrastructure sensor data (including image data)at the smart infrastructure controller; analyze the LIDAR data and/orthe smart infrastructure sensor data to detect the individual or thefirst location of the individual; analyze the LIDAR data and/or thesmart infrastructure sensor data to detect a direction of movement ofthe individual; analyze the LIDAR data and/or the smart infrastructuresensor data to detect (i) the one or more obstacles in front of thedirection of movement of the individual, and/or (ii) the second locationof the one or more obstacles in front of the direction of movement ofthe individual; generate or provide navigation feedback to theindividual to avoid the one or more obstacles and/or move about basedupon (i) the first location of the individual, (ii) the direction ofmovement of the individual, and/or (iii) the second location of the oneor more obstacles in front of the direction of movement of theindividual.

The one or more processors, transceivers, sensors, and/or servers, maybe configured to receive the LIDAR data via wireless communication ordata transmission over one or more radio frequency links.

In yet another aspect, a computer system configured to provide firstnotice of loss may be provided. The computer system may include: one ormore processors; and a program memory coupled to the one or moreprocessors and storing executable instructions that when executed by theone or more processors cause the computer system to: (1) receive lightdetection and ranging (LIDAR) data generated from a LIDAR camera; (2)detect, within the LIDAR data: (i) the human individual, (ii) a firstlocation of the human individual, (iii) one or more obstacles, and (iv)a second location of the one or more obstacles; and (3) providenavigation feedback to the human individual based upon the LIDAR data,the first location of the individual, and/or the second location of theone or more obstacles as determined from the LIDAR data to facilitateproviding navigation assistance to the human individual. The system mayinclude additional, less, or alternate functionality, including thatdiscussed elsewhere herein.

For instance, the navigation feedback may be auditory, and comprisedirection and distance instructions to guide the individual and avoidthe one or more obstacles.

The computer system may be further configured, via the one or moreprocessors, sensors, servers, and/or transceivers, to: (1) receive theLIDAR data at a smart home controller, such as via wirelesscommunication or data transmission over one or more radio frequencylinks; (2) receive, at the smart home controller, smart home sensor dataincluding image data; (3) analyze the LIDAR data and/or the smart homesensor data to detect the individual or the first location of theindividual within or about a home; (4) analyze the LIDAR data and/or thesmart home sensor data to detect a direction of movement of theindividual within or about the home; (5) analyze the LIDAR data and/orthe smart home sensor data to detect (i) the one or more obstacles infront of the direction of movement of the individual within or about thehome, and/or (ii) the second location of the one or more obstacles infront of the direction of movement of the individual within or about thehome; and (6) generate and provide navigation feedback to the individualto avoid the one or more obstacles and/or move about the home based upon(i) the first location of the individual, (ii) the direction of movementof the individual, and/or (iii) the second location of the one or moreobstacles in front of the direction of movement of the individual. Thenavigation feedback may be auditory, and comprise direction and distanceinstructions to guide the individual and avoid the one or moreobstacles.

Other Matters

Although the text herein sets forth a detailed description of numerousdifferent embodiments, it should be understood that the legal scope ofthe invention is defined by the words of the claims set forth at the endof this patent. The detailed description is to be construed as exemplaryonly and does not describe every possible embodiment, as describingevery possible embodiment would be impractical, if not impossible. Onecould implement numerous alternate embodiments, using either currenttechnology or technology developed after the filing date of this patent,which would still fall within the scope of the claims.

It should also be understood that, unless a term is expressly defined inthis patent using the sentence “As used herein, the term ‘______’ ishereby defined to mean...” or a similar sentence, there is no intent tolimit the meaning of that term, either expressly or by implication,beyond its plain or ordinary meaning, and such term should not beinterpreted to be limited in scope based upon any statement made in anysection of this patent (other than the language of the claims). To theextent that any term recited in the claims at the end of this disclosureis referred to in this disclosure in a manner consistent with a singlemeaning, that is done for sake of clarity only so as to not confuse thereader, and it is not intended that such claim term be limited, byimplication or otherwise, to that single meaning. Finally, unless aclaim element is defined by reciting the word “means” and a functionwithout the recital of any structure, it is not intended that the scopeof any claim element be interpreted based upon the application of 35U.S.C. § 112(f).

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Additionally, certain embodiments are described herein as includinglogic or a number of routines, subroutines, applications, orinstructions. These may constitute either software (code embodied on anon-transitory, tangible machine-readable medium) or hardware. Inhardware, the routines, etc., are tangible units capable of performingcertain operations and may be configured or arranged in a certainmanner. In example embodiments, one or more computer systems (e.g., astandalone, client or server computer system) or one or more hardwaremodules of a computer system (e.g., a processor or a group ofprocessors) may be configured by software (e.g., an application orapplication portion) as a hardware module that operates to performcertain operations as described herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that is permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC) toperform certain operations). A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. Considering embodiments inwhich hardware modules are temporarily configured (e.g., programmed),each of the hardware modules need not be configured or instantiated atany one instance in time. For example, where the hardware modulescomprise a general-purpose processor configured using software, thegeneral-purpose processor may be configured as respective differenthardware modules at different times. Software may accordingly configurea processor, for example, to constitute a particular hardware module atone instance of time and to constitute a different hardware module at adifferent instance of time.

Hardware modules can provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multipleof such hardware modules exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the hardware modules. In embodiments in whichmultiple hardware modules are configured or instantiated at differenttimes, communications between such hardware modules may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware modules have access. Forexample, one hardware module may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware module may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processor-implemented. For example, at least some of theoperations of a method may be performed by one or more processors orprocessor-implemented hardware modules. The performance of certain ofthe operations may be distributed among the one or more processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processor or processors maybe located in a single location (e.g., within a home environment, anoffice environment or as a server farm), while in other embodiments theprocessors may be distributed across a number of geographic locations.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein any reference to “one embodiment” or “an embodiment”means that a particular element, feature, structure, or characteristicdescribed in connection with the embodiment may be included in at leastone embodiment. The appearances of the phrase “in one embodiment” invarious places in the specification are not necessarily all referring tothe same embodiment.

Some embodiments may be described using the expression “coupled” and“connected” along with their derivatives. For example, some embodimentsmay be described using the term “coupled” to indicate that two or moreelements are in direct physical or electrical contact. The term“coupled,” however, may also mean that two or more elements are not indirect contact with each other, but yet still co-operate or interactwith each other. The embodiments are not limited in this context.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

In addition, use of the “a” or “an” are employed to describe elementsand components of the embodiments herein. This is done merely forconvenience and to give a general sense of the description. Thisdescription, and the claims that follow, should be read to include oneor at least one and the singular also includes the plural unless it isobvious that it is meant otherwise.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs for theapproaches described herein. Thus, while particular embodiments andapplications have been illustrated and described, it is to be understoodthat the disclosed embodiments are not limited to the preciseconstruction and components disclosed herein. Various modifications,changes and variations, which will be apparent to those skilled in theart, may be made in the arrangement, operation and details of the methodand apparatus disclosed herein without departing from the spirit andscope defined in the appended claims.

The particular features, structures, or characteristics of any specificembodiment may be combined in any suitable manner and in any suitablecombination with one or more other embodiments, including the use ofselected features without corresponding use of other features. Inaddition, many modifications may be made to adapt a particularapplication, situation or material to the essential scope and spirit ofthe present invention. It is to be understood that other variations andmodifications of the embodiments of the present invention described andillustrated herein are possible in light of the teachings herein and areto be considered part of the spirit and scope of the present invention.

While the preferred embodiments of the invention have been described, itshould be understood that the invention is not so limited andmodifications may be made without departing from the invention. Thescope of the invention is defined by the appended claims, and alldevices that come within the meaning of the claims, either literally orby equivalence, are intended to be embraced therein.

It is therefore intended that the foregoing detailed description beregarded as illustrative rather than limiting, and that it be understoodthat it is the following claims, including all equivalents, that areintended to define the spirit and scope of this invention.

Furthermore, the patent claims at the end of this patent application arenot intended to be construed under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in the claim(s). Thesystems and methods described herein are directed to an improvement tocomputer functionality, and improve the functioning of conventionalcomputers.

What is claimed:
 1. A computer-implemented method for generating anelectronic inventory list of personal belongings, comprising, via one ormore processors, transceivers, sensors, and/or servers: receiving lightdetection and ranging (LIDAR) data generated from one or more LIDARcameras; analyzing the LIDAR data to determine or identify one or morepersonal articles or insurable assets; and generating an electronicinventory list of personal belongings based upon the one or morepersonal articles or insurable assets determined or identified from theLIDAR data; and wherein generating the electronic inventory listincludes, via the one or more processors, transceivers, sensors, and/orservers, processor analysis of: (i) the LIDAR data, and (ii) one or moreadditional sources of data including: smart home sensor data and/orimages; and/or smart infrastructure data and/or images.
 2. Thecomputer-implemented method of claim 1, wherein the one or moreadditional sources of data include the smart home sensor data and/orimages.
 3. The computer-implemented method of claim 1, the methodfurther comprising, via the one or more processors, transceivers,sensors, and/or servers, generating an electronic personal articlesinsurance quote covering several personal articles identified fromprocessor analysis of the LIDAR data and listed within the electronicinventory list.
 4. The computer-implemented method of claim 3, themethod further comprising, via the one or more processors, transceivers,sensors, and/or servers, transmitting the electronic personal articlesinsurance quote to the mobile device of the customer via wirelesscommunication and/or data transmission over one or more radio frequencylinks for the customer’s review, modification, and/or approval.
 5. Thecomputer-implemented method of claim 1, wherein the one or moreadditional sources of data include the smart infrastructure data and/orimages.
 6. The computer-implemented method of claim 1, wherein theelectronic inventory list includes one or more electronic devices,televisions, furniture, antiques, and/or paintings.
 7. Thecomputer-implemented method of claim 1, wherein the LIDAR data isreceived via wireless communication or data transmission over one ormore radio frequency links.
 8. A computer system configured to generatean electronic inventory list of personal belongings, the computer systemcomprising one or more processors, transceivers, sensors, and/or serversconfigured to: receive light detection and ranging (LIDAR) datagenerated from one or more LIDAR cameras; analyze the LIDAR data todetermine or identify one or more personal articles or insurable assets;and generate an electronic inventory list of personal belongings basedupon the one or more personal articles or insurable assets determined oridentified from the LIDAR data; and wherein generating the electronicinventory list includes, via the one or more processors, transceivers,sensors, and/or servers, processor analysis of: (i) the LIDAR data, and(ii) one or more additional sources of data including: smart home sensordata and/or images; and/or smart infrastructure data and/or images. 9.The computer system of claim 8, wherein the one or more additionalsources of data include the smart home sensor data and/or images. 10.The computer system of claim 8, the system further configured to, viathe one or more processors, transceivers, sensors, and/or servers,generate an electronic personal articles insurance quote coveringseveral personal articles identified from processor analysis of theLIDAR data and including personal articles listed in the electronicinventory list.
 11. The computer system of claim 10, the system furtherconfigured to, via the one or more processors, transceivers, sensors,and/or servers, transmit the electronic personal articles insurancequote to the mobile device of the customer via wireless communicationand/or data transmission over one or more radio frequency links forcustomer review, modification, and/or approval.
 12. The computer systemof claim 8, wherein the one or more additional sources of data includethe smart infrastructure data and/or images.
 13. The computer system ofclaim 8, wherein the electronic inventory list includes one or moreelectronic devices, televisions, furniture, antiques, and/or paintings.14. The computer system of claim 8, the system further configured to,via the one or more processors, transceivers, sensors, and/or servers,receive the LIDAR data via wireless communication or data transmissionover one or more radio frequency links.
 15. A computer system forgenerating an electronic personal articles insurance quote, comprising:one or more processors; and a program memory coupled to the one or moreprocessors and storing executable instructions that when executed by theone or more processors cause the computer system to: receive lightdetection and ranging (LIDAR) data generated from one or more LIDARcameras; analyze the LIDAR data to determine or identify one or morepersonal articles or insurable assets; and generate an electronicinventory list of personal belongings based upon the one or morepersonal articles or insurable assets determined or identified from theLIDAR data; and wherein the executable instructions further cause thecomputer system to generate the electronic inventory list via analysisof: (i) the LIDAR data, and (ii) one or more additional sources of dataincluding: smart home sensor data and/or images; and/or smartinfrastructure data and/or images.
 16. The computer system of claim 15,wherein the one or more additional sources of data include the smarthome sensor data and/or images.
 17. The computer system of claim 15,wherein the one or more additional sources of data include the smartinfrastructure data and/or images.
 18. The computer system of claim 15,wherein the executable instructions further cause the computer system togenerate an electronic personal articles insurance quote coveringseveral personal articles identified from processor analysis of theLIDAR data and including personal articles listed in the electronicinventory list.
 19. The computer system of claim 18, wherein theexecutable instructions further cause the computer system to transmitthe electronic personal articles insurance quote to the mobile device ofthe customer via wireless communication and/or data transmission overone or more radio frequency links for customer review, modification,and/or approval.
 20. The computer system of claim 15, wherein theelectronic inventory list includes one or more electronic devices,televisions, furniture, antiques, and/or paintings.